Accounts Receivable Process Mining Guide

Accounts Receivable Process Mining: Understand DSO

Days sales outstanding (DSO) estimates the average number of days between a sale and payment. If DSO changes, seasonality may be part of the explanation. So can the accounts receivable process: invoices may wait for follow-up, disputes may take time to resolve, and rework can delay cash application. Process mining shows where these steps add time, without assuming customer behavior is the only factor.

What can process mining show in accounts receivable?

Your procedures describe how collections should work. An event log shows how the process actually runs: the activities, handoffs, waiting times, and paths taken by different cases.

With ProcessMind, you can analyze accounts receivable data to find:

• Time from invoice creation to payment
• Waiting time between dunning and other collection activities
• Dispute rates and resolution times by customer, region, or invoice type
• Rework, such as repeated invoice handling or corrections
• Manual activities and handoffs
• Differences between the documented process and actual execution
• Cases that miss collection or resolution targets

These findings help you distinguish process delays from other factors that affect DSO. They do not prove that a process change will produce a specific DSO result.

Where do collection delays and rework occur?

Start with the stages between invoice creation and payment. A process map shows where cases wait, which paths take longer, and where teams repeat work. Filter by customer segment, invoice type, payment status, or dispute reason to compare similar cases.

For example, check whether disputed invoices wait longer for resolution, whether teams handle certain invoice types more than once, or whether a handoff is followed by a long delay. The event log shows process timing and sequence, but it cannot explain every cause on its own.

Explore Process Mining to see how process maps, variants, and filters can support your analysis.

How do disputes and cash application affect the picture?

Disputes can add time and work between invoicing and payment. Compare dispute types, resolution paths, and elapsed time to see where cases wait or return to earlier activities. Rework can also add time when invoices need repeated review or correction.

Cash application is another area to examine. Look at when payment-related activities occur and how they connect to invoice handling and dispute resolution. Process mining analyzes recorded events; it does not collect payments.

How should you interpret the accounts receivable turnover ratio?

Accounts receivable turnover measures how often receivables are collected over a period. It offers a different view from DSO: turnover measures collection frequency, while DSO estimates the average time between a sale and payment. Use the definitions and calculation conventions your finance team already follows when comparing these measures.

Process mining adds context about how work gets done alongside these financial metrics. It can help you investigate whether delays, disputes, or rework coincide with changes in collection performance, but it does not replace your finance team’s definitions or accounting analysis.

Accounts receivable vs accounts payable: how the two cycles differ

Accounts receivable tracks what customers owe your organization and the work involved in collecting it. Accounts payable tracks what your organization owes suppliers and the work involved in paying them. The processes have different goals and events, but both benefit from visibility into actual process paths, waiting times, handoffs, and rework.

Compare with the accounts payable use case, or see the finance and shared services use case for a broader look at process analysis across finance operations.

How can you analyze your collections process?

1. Mine: Prepare an event log and analyze the actual process in ProcessMind. Compare paths and filter by attributes such as customer segment, invoice type, payment status, or dispute reason.
2. Model: Use your findings to document a target process in BPMN. Define activities, handoffs, exception paths, and the KPIs your team wants to track. Explore BPMN modeling to document current and future states.
3. Simulate: Compare proposed process scenarios before implementation. For example, assess different reminder timing, dispute routing, approval rules, or handoffs. Learn about process simulation to explore how scenarios may affect process performance.

ProcessMind analyzes and models process data. Your team decides which changes to implement and monitors the results.

What data do you need to get started?

Start with a collections question, such as where invoice-to-payment time increases or which dispute paths involve the most rework. For an initial analysis, use an invoice and payment log you already export from your ERP.

At minimum, prepare:

• A case ID that links events to an invoice or another case
• An activity name
• A timestamp for each event

Where available, add attributes such as customer, invoice value, payment status, dispute reason, team, and region. These fields let you compare segments and investigate differences in process performance.

Check the data requirements before preparing your event log.

What results should you expect?

Results depend on your data quality and coverage, process complexity, and the changes your team makes. Use your event log to establish a baseline, find where time and rework accumulate, and track process performance after changes.

Process mining does not guarantee a reduction in DSO. It shows how recorded work flows and helps your team investigate and prioritize opportunities. Financial outcomes depend on multiple factors.