Debt Analytics: Overdue Receivables by Ageing Band, Customer and Sales Manager

The total amount owed rarely tells you much. What matters is not just how much you are owed, but how long that debt has been outstanding. This report breaks overdue receivables down by how late they are: up to 30 days, 31–60, 61–90 and over 90 days.

Debt analytics — sample Power BI report

Which decisions it helps you make

  • Which debts to chase first. Debts over 90 days old are the most likely never to be paid.
  • Whose credit to restrict. A customer whose debt keeps sliding into the later bands is a warning sign.
  • How your sales managers are performing. Debt by sales manager shows whose customer portfolio is building up overdue balances.
  • How much cash is actually tied up. The ratio of overdue to not-yet-due receivables shows how much working capital is sitting idle.

What you see in the report

  • an overall debt summary by ageing band;
  • overdue and not-yet-due amounts, plus the total receivables balance;
  • late payments by sales manager, broken down into ageing bands;
  • late payments by customer, with customer code and name;
  • a list of potential bad debtors;
  • the ability to see which sales manager’s customers are overdue.

How to read this report

Look at how debts move between the bands over time, rather than at a single month’s snapshot. If the amount in the “61–90 days” band grows every month, your earlier collection stage is not working.

Second, set each customer’s debt against their turnover. High turnover combined with large overdue balances does not make a good customer — it is unpaid credit.

For day-to-day control, the late payments report is a better fit, as it shows the individual invoices and the number of days each is overdue.

Why ageing bands rather than the total

A debt loses value with every month that passes. In practice, the likelihood of recovering the money falls off roughly as follows:

  • up to 30 days — almost all debts are paid;
  • 31–60 days — still under control, but active follow-up is needed;
  • 61–90 days — some debts can no longer be recovered without legal action;
  • over 90 days — the chance of recovery is slim, and the process itself often costs more than the amount owed.

That is why the key measure in the report is not the total, but how the money moves between the bands. A growing “61–90 days” band means the earlier stage is not working — and that is a management problem, not a customer problem.

Debt by sales manager

The breakdown by sales manager is often the most uncomfortable view, but also the most useful. It answers a question nobody otherwise asks: were the sales figures achieved by selling to customers who actually pay?

A sales manager who leads on turnover but also has the most overdue debt is in reality bringing in less than it appears. If bonuses are calculated on turnover rather than on paid invoices, this situation is built into the system.

This view is usually what prompts a change to the incentive scheme — replacing turnover with cash collected.

How much cash is actually tied up

It is worth turning the receivables balance into a single, easy-to-grasp number: how many days of turnover it represents. If monthly turnover is €200,000 and receivables stand at €300,000, the company is permanently financing its customers to the tune of a month and a half’s turnover.

The same cash is often sitting in the warehouse too — the slow-moving stock report shows how much. Taken together, the two figures explain why a profitable company can have no money in the bank.

How to get this report

Debt analytics is included in the Rivilė PRO and Finvalda PRO report packages — find out more on the pricing page.

Further reading

Want reports like these for your own business?

Analitika360 builds Power BI reports from the data already in your accounting system — Rivilė, Finvalda or R-Keeper. They refresh automatically, from €59 a month.

Pricing and plans
Analitika360 client stories

Data that helps you decide

See how companies like yours put Analitika360 reports to work in Power BI.

“
We took the standard R-Keeper report package and they tailored it to us on top of that. It all just works.
TB
Tomas B.restaurant owner
“
Twenty ready-made reports — we didn't have to work out what to ask for. Our Finvalda data is finally something you can look at. Recommended.
IM
Ingrida M.accountant
“
What we liked was that Analitika360 already had a 20-report package for Rivilė users — we didn't have to work out our requirements from scratch. We were up and running quickly, and later they adapted several reports to the specifics of our production. It saved us both time and money.
MK
Marius K.finance director
“
We are a group of companies running Rivilė, and consolidated reporting was always a headache. Analitika360 started from the standard 20-report package and then fitted it to our group structure — we now see everything in one Power BI model, and it refreshes itself.
GJ
Giedrė Jankauskaitėfinancial accountant
“
We run six restaurants on R-Keeper and had long been looking for a way to compare results across sites. The standard 20-report package covered most of what we needed, and reports specific to our group were added later.
AŠ
Andrius Š.director of a restaurant group
“
We came to them on a recommendation, and the ready-made 20-report standard for Finvalda users was a pleasant surprise straight away. Management now gets a clear financial picture every Monday, and I no longer spend days exporting data into Excel.
RP
Rasa Petrauskienėhead of accounting
“
We use Rivilė, but we never had time to build reports from scratch. The 20-report package was exactly what we needed — we had it running within a week.
VP
Vaidas P.retail chain manager
“
We have four cafés on R-Keeper and for a long time we ran them on gut feel. The Analitika360 reports showed us things we had simply never noticed. We now decide on the numbers rather than on guesswork.
LK
Laura Kazlauskienėfinance director of a café group