Improve accounts receivable management with data and AI
Improve receivables management with DSO, an aging analysis and payment behavior per customer. See sooner who to call so your cash comes in faster.
By Auke Westra
Founder of DigiData
Short answer
Good receivables management starts with three figures from your accounting system: DSO (how many days of revenue are outstanding), an aging analysis of open invoices and average payment behavior per customer. Review them weekly, personally call the largest overdue items and adjust payment terms or deposits for customers who consistently pay late. Automate the overview so it is ready every week.
Open invoices are an interest-free loan to your customer
Every day a customer pays later, you finance their business. With annual revenue of EUR 2 million, each extra day of payment term ties up roughly EUR 5,500. A ten-day difference in payment behavior is EUR 55,000 of working capital.
In the Netherlands the rules are clear. According to the government portal Ondernemersplein, large companies must pay SMEs within 30 days, the maximum term between businesses is 60 days, and a 30-day term applies when nothing was agreed. In practice these terms are often exceeded, and a small business only notices when the bank balance gets tight.
Improving receivables management is therefore mostly about seeing sooner what is outstanding and acting in a more targeted way. The data for that is already in your accounting system.
Metric 1: DSO
DSO (days sales outstanding) shows how many days of revenue are outstanding with customers on average:
DSO = outstanding receivables ÷ revenue in the period × days in the period
Example: EUR 67,000 outstanding, EUR 122,000 revenue in August, 31 days. DSO = 67,000 ÷ 122,000 × 31 = 17 days. This is the same fictional example as in the financial dashboard, where you can download the data.
Watch two things. Use the closing balance of the period for receivables, not a sum across months. And use the same basis for revenue as for receivables: if open items include VAT, calculate with revenue including VAT as well, or your DSO will look higher than it is.
The trend matters more than the value. A DSO that climbs from 38 to 49 days over three months is a signal, even if 49 days does not look alarming on its own.
Metric 2: aging analysis
An aging analysis groups open items by age:
| Age | Amount | Share | Action |
|---|---|---|---|
| Not yet due | EUR 41,000 | 61% | None |
| 1–30 days overdue | EUR 15,500 | 23% | Automatic reminder |
| 31–60 days overdue | EUR 7,000 | 10% | Personal phone call |
| More than 60 days overdue | EUR 3,500 | 5% | Formal notice, payment plan or collection |
Fictional example.
The table shows where the money is tied up and what action goes with it. The Dutch Chamber of Commerce (KVK) offers practical tips on reminders and formal notices; see the sources below.
Metric 3: payment behavior per customer
The average DSO hides large differences between customers. So calculate, per customer, the average number of days between due date and payment over the past twelve months. You usually find three groups:
- Punctual payers. No action needed.
- Consistently late payers with small balances. An automatic reminder is enough.
- Consistently late payers with large balances. This is where the money is. Discuss a shorter term, milestone invoicing or a deposit on the next job.
That third group is often only five to ten customers. Targeting them lowers DSO more than sending reminders to everyone.
Want to see your own aging analysis and payment behavior per customer? Request a 20-minute demo. We connect your accounting system and show who consistently pays late.
How to automate the overview
Many accounting packages have a list of open items, but no trend, no payment behavior per customer and no combination with other data. By connecting your accounting system, for example Exact Online, Twinfield or Moneybird, you have current sales invoices with invoice and due dates in one place every morning. Which fields are available varies by package; check the connector page.
Then you can:
- build a dashboard with the DSO trend and aging analysis;
- send an automated email overview every Monday to whoever calls customers, with the ten largest overdue items;
- analyze further in Power BI or Excel through OData.
Where AI helps
An AI agent on your connected accounting data answers follow-up questions that do not fit a standard report:
- "Which customers pay later on average this year than last year?"
- "Which overdue invoices belong to projects that have already been delivered?"
- "How much of our outstanding receivables sits with the five largest customers?"
The answer comes from the same figures as the dashboard, so you can check it. The decision stays with you: AI helps you see sooner where to start, not who gets a formal notice.
Make it a weekly routine
Block fifteen minutes a week for receivables. Review the DSO trend, call the three largest items more than 30 days overdue and note the agreement. After a quarter, you see the effect in your DSO and your bank balance. Link it to your cash flow forecast to see what a missing payment means for the coming weeks.
Sources

About Auke Westra
Founder of DigiData
Auke Westra is Founder of DigiData and writes about data integrations, OData and Power BI.
Ready to start?
Try DigiData for free for 14 days. Connect your software, load your data into Power BI and discover the difference.
Please contact usRelated articles
KPI dashboard for SMBs: 12 examples with formulas
See 12 KPIs for a small business dashboard, each with a formula, source and action. Includes free sample data so you can build your own KPI dashboard.
Automate job costing: margin per project without Excel
Automate job costing with connected hours, materials and invoices. See the gap between estimate and actuals for each project while it is still running.
How to build a cash flow forecast from your accounting data
Build a 13-week cash flow forecast from open invoices, fixed costs and VAT in your accounting system. Includes a worked example, pitfalls and a routine.
Connect HubSpot CRM to Power BI via OData
Connect HubSpot to Power BI with an OData setup guide and sample deal measures. Learn which CRM tables are available and how to model your sales reports.