Accounts Payable Process Mining Guide

Find delays in your accounts payable process

Upload your event log to see how accounts payable actually runs: where invoices wait, which paths they take, and how often work is repeated or blocked. Measure invoice cycle time, touchless rate, and exception rate from event data, then compare options such as changing approval rules or adding capacity.

Why analyze accounts payable?

AP teams manage high invoice volumes, approvals, exceptions, and payments. Delays can mean late payments, strained supplier relationships, and rework. Standard reports often show totals but not where time accumulates or which invoice paths generate the most exceptions.

Process knowledge may be spread across procedures, system reports, and team experience. Process mining brings event data together to show how work actually flows, so you can investigate delays with evidence instead of assumptions.

Which three AP measures should you track?

Start with three measures your finance team can understand and act on:

Set consistent definitions for the start, end, and qualifying activities before comparing results. For example, decide whether cycle time ends at approval or payment, and which activities count as manual intervention. Consistent definitions make the measures useful across teams and reporting periods.

Accounts payable vs accounts receivable: how the two cycles differ

Accounts payable tracks what your organization owes suppliers and the work involved in paying them. Accounts receivable tracks what customers owe your organization and the work involved in collecting it. Both run on the same document and the same rules (a purchase order or a sales invoice, a match, an approval, a payment), but in opposite directions, and both are measured against the terms you agreed.

Process mining reads the two cycles the same way. It reconstructs the path each invoice takes, so you can compare the terms you set with the time the work actually took, and see where waiting, rework or exceptions accumulate. Accounts receivable process mining covers the collections side.

Where does invoice cycle time go?

Total cycle time includes active work and waiting. Process mining for accounts payable lets you trace each invoice through its recorded activities and see where queues build up.

Common patterns to investigate include:

• Approval queues: An approval task may take minutes, while the invoice waits days for an approver.
• Blocked or parked invoices: A purchase order mismatch can hold an invoice even when the system records it with a valid status.
• Supplier master data issues: Missing or mismatched vendor details may require manual correction before processing can continue.
• Duplicate submissions: An invoice submitted through multiple channels may trigger extra checks and rework.
• Three-way match exceptions: Compare exceptions by supplier, invoice type, or other available attributes to see where they cluster.

A high exception rate alone does not explain the cause. Use invoice paths and timestamps to find which exceptions lead to the longest waits or the most repeated work.

How can you investigate touchless processing and exceptions?

Use the event log to distinguish invoices that follow the expected path from those that need intervention. Review the activities recorded for each case, including validation, matching, approval, blocking, and payment.

For three-way match exceptions, compare invoices that pass on the first attempt with those that need correction or additional review. Check where the exception occurs, how long the invoice waits afterward, and whether the pattern recurs for specific suppliers or invoice types. This helps you focus on exceptions that affect cycle time instead of treating them all as equally important.

What data do you need?

Start with an event log from your ERP or invoice management system. Each row should include a case ID that identifies the invoice, an activity name, and a timestamp. Add relevant attributes when available, such as supplier, invoice type, amount, approval status, and payment date.

Your data should link activities to the same invoice and put them in chronological order. Check how your source system records statuses and timestamps, because those definitions affect the measures you calculate.

See what data you need

For a practical guide to preparing and reviewing your event log, see the process mining data documentation.

How can you compare approval or staffing changes?

Once you understand the current flow, use process simulation to compare potential changes before you make them. For example, compare your current approval rules with a scenario that changes approval routing, or compare current capacity with a scenario that adds capacity at a constrained step.

Review each scenario using the same measures, such as cycle time, touchless rate, and exception rate. Treat the results as comparable options based on your assumptions, not guaranteed outcomes. The comparison can help you decide which changes to investigate and understand the trade-offs.

How do you get started with AP process mining?

Choose one question to investigate, such as why invoices miss payment terms or where rework enters the flow. Prepare an event log with invoice IDs, activities, timestamps, and attributes relevant to your question. Upload the extract to ProcessMind, then review the main process paths, queues, and exceptions.

Use your findings to decide what to examine next, document a target process, or compare scenarios. Process mining shows what your recorded data supports, and results depend on the data and assumptions you use.

See how the analysis works step by step

Upload one AP extract to see the flow

Your AP data is already in your ERP. Start with one extract and use the trial to see how invoices move through your process.

Upload one AP extract to see the flow