Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
YOUR CASH COLLECTION KPIs ARE WRONG. HERE’S WHY
If you’re a Collections Manager or Finance Director, you will be keen to drive improved cash collection performance from your teams. You may also be keen to monitor how those improvements are being realised over time. You probably join the majority of others by using the traditional, recognised metrics like DSO (Days’ Sales Outstanding), Overdue AR, Overdue %, Ageing, and maybe even CEI (Collections Effectiveness Index).
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections performance for your business, your analysis needs to be underpinned by calculations at an invoice level. Even if you have many millions of invoices per annum, that’s where you need to go, and that is not easy to be doing on a daily basis. If you can calculate the various timings for each and every invoice, each day, however, you can aggregate the calculations into whichever grouping you need, to understand exactly how long any given timeline may be, e.g. precisely how long a customer takes to pay you versus due date over a given period or geography, or how long it takes to collect for a customer segment past a given dunning action, for example.
And there’s another step of complexity to it.
Each of those calculations needs to be weighted by the value (or outstanding value) of the respective invoice. If you don’t add this to your calculations, you will have straight averages for your timings that ignore the value of each invoice, and therefore do not reflect cash movements. With value-weighted averages, you can then aggregate the mathematically correct averages across any group of invoices, and understand exactly what the timings are all along the Order to Cash process.
The good news is that POP Collect includes an unparalleled suite of best-in-class metrics, analytics and visuals, so business performance can be understood each and every day, from high-level through to invoice-level, with cash improvement opportunities measured and monitored through powerful, AI-enabled BI.
With POP, dispute management root cause resolution, credit risk, dunning process optimisation, collector workload and performance monitoring, invoicing quality and timeliness, payment terms compliance and enhancement, and detailed cash collections performance are all part of the standard set of tools and visuals.
Contact us for a free demo and to understand why POP will take you to record cash collection performance, while saving significant costs.
Unfortunately, these are the wrong KPIs.
But why?
The first thing to note is the above list are all based on point-in-time, balance sheet figures. That means that if you are tracking the month-end figure in your reporting, you are ignoring performance for the other 30 or so days in the month. In other words, you are encouraging monthly, cyclical behaviours within your teams, and are also highly vulnerable to results being skewed by point-in-time outliers.
The typical unseen outcome is a classic hockey-stick effect of collections behaviour (Figure 1), whereby chasing customers for payment is slower in the first half of any given month and picks up more and more towards the end of the month to improve that month-end KPI. By definition, you are therefore not collecting cash with the same timeliness as if you were measured daily, and are also unable to understand daily cash movements with accuracy without going into invoice-level, manual forecasting. These high-level metrics are also not drillable without being recalculated each time, i.e. you cannot see the high-level DSO, and then say, for example, let’s look at how DSO is affected by dispute type A, or by customer group 1, etc. Only by drilling into the numbers where needed, can you truly understanding root causes and improvement opportunities.
Figure1. In-Month Collections Hockey Stick
So why does everybody seem to use these KPIs? The main reason is simple: it’s all you’ve got. And if DSO and Overdue % are how you’ve always measured performance, then why look for something different? The consequence is that your understanding of performance will always be limited.
This patchwork of manually-produced spreadsheets also takes time to pull together, is error-prone, and may end up as different versions with different users. If you’re really lucky, however, you may already have one of the available collections software products to calculate these very same KPIs for you each month.
Unfortunately, regardless of how your KPIs are being produced, they are still the wrong KPIs!
Thankfully, there is another way; a way that reveals performance on a daily basis, and enables you to cut and slice the data to truly understand where cash is being tied up, how performance differs by customer, collector, business unit, dispute type, or any other relevant grouping.
In fact, it is probably time to assign your old software or spreadsheets to the history books, and get the right KPIs in place to drive real performance improvement and record cash collections.
So what should you be measuring and monitoring, and how can you do it?
Firstly, the bad news.
To truly understand Cash Collections perfor