Switching to e-invoicing is supposed to make accounts payable faster, cheaper, and less error-prone. Whether it actually does depends on how you measure it. Teams that track the right numbers before they start can quantify what changed. Teams that do not measure tend to run on impressions — which are usually optimistic and rarely reliable.
These are the metrics that genuinely tell you how your AP process is performing and whether the investment in e-invoicing is delivering.
Processing cost per invoice
This is the most important number, and the one most AP teams have never actually calculated. It combines direct costs (software licences, bank transaction fees) with indirect costs (staff time across all invoice-related activities, divided by invoice volume). Industry benchmarks for Switzerland put fully manual processing at CHF 15–25 per invoice. Straight-through processing of a structured e-invoice sits at CHF 1–3.
Calculate your baseline before switching. The simplest approach is to estimate the total AP team hours spent on invoice-related work in a month — data entry, chasing approvals, resolving exceptions, filing — and multiply by the loaded hourly cost. Divide by your monthly invoice volume. That is your current per-invoice cost.
Track it quarterly after the switch. The number will not drop immediately — it takes time for supplier adoption to reach the point where a meaningful share of invoices arrive as structured data. But if it is not moving in the right direction after six months, something in the implementation is not working as it should.
Straight-through processing rate (STP rate)
The STP rate is the percentage of invoices that go from receipt to payment approval without any manual intervention. An invoice that matches its purchase order and goods receipt automatically, gets approved by a rule rather than a human, and is queued for payment without anyone touching it counts as straight-through.
A realistic starting STP rate for a company migrating from paper and PDF is 20–30%. After a year of structured e-invoicing, with supplier adoption growing and matching rules tuned, 60–70% is a reasonable target. Companies with very clean data and high supplier compliance reach 80%+.
Track this as a ratio: STP invoices divided by total invoices received, per month. Segment it by invoice type and supplier if your system allows — knowing that 90% of your structured e-invoices process straight-through while 15% of PDF invoices do helps you prioritise supplier onboarding conversations.
Exception rate
The exception rate is the inverse complement of STP: the percentage of invoices that require manual intervention. Every exception costs staff time. Exceptions cluster around a few root causes — price mismatches, missing PO references, quantity discrepancies — and tracking which category generates the most exceptions tells you where to focus your attention.
A high exception rate among structured e-invoices specifically (as opposed to PDFs) usually points to a data quality problem: supplier master data is inconsistent, PO references are not being communicated to suppliers, or your three-way matching tolerances are set too tight. A high exception rate among PDFs is expected and is an argument for accelerating supplier migration.
Invoice cycle time
Cycle time measures how long it takes from invoice receipt to payment approval. This is distinct from days payable outstanding — it is not about when you choose to pay, but about how quickly the invoice moves through your process.
Long cycle times indicate bottlenecks. An invoice that sits in an approval queue for eight days is not a payment timing decision; it is a process failure. Tracking average cycle time by invoice type (structured vs PDF), by approver, and by department exposes where the delays actually are.
The target varies by invoice type. A structured e-invoice that clears three-way matching should reach payment approval within one working day in a well-configured system. A non-PO invoice requiring a cost centre owner to review it might reasonably take two to three days. An invoice sitting for more than five working days is a red flag worth investigating.
Supplier e-invoicing adoption rate
This metric tracks the percentage of your supplier base sending invoices in a structured format — eBill, PEPPOL, or ZUGFeRD — rather than PDF or paper. It is a leading indicator for STP rate. If your adoption rate is low, your STP rate will stay low regardless of how well your internal systems are configured.
Track it as a percentage of invoice volume, not just a count of suppliers. Your top 20 suppliers may account for 60% of your invoice volume. Converting those 20 to structured formats has a much larger effect on your processing than converting 200 smaller suppliers.
Set a target adoption rate and run an active supplier onboarding programme to reach it. Adoption does not happen passively — suppliers need to be told what formats you accept, given a clear path to switch, and followed up with if they do not.
Duplicate invoice rate
Duplicate invoices — the same invoice submitted twice — are one of the most preventable sources of overpayment in AP. They happen when a supplier resends an invoice after not receiving a payment confirmation, when a PDF arrives by email and the same invoice also comes through a structured channel, or when different branches of the same supplier submit independently.
A structured e-invoice pipeline should catch duplicates automatically by checking the invoice number, supplier ID, and amount against previously processed invoices. Track the rate at which duplicates are caught before payment and the rate at which they slip through (discovered later via reconciliation or supplier query). Any duplicate that gets paid is expensive to recover.
Cost of late payments
Late payment charges and lost early payment discounts are real costs that rarely appear in AP team reporting but show up in the P&L. Track the number of invoices paid after their due date, the value of any late payment fees incurred, and the value of early payment discounts available versus discounts taken.
An AP process with long cycle times and high exception rates will have a worse late payment record than one running smoothly. Making this cost visible — connecting it to the process metrics rather than treating it as a finance abstraction — gives the AP team a direct line between process improvement and bottom-line impact.
Bringing it together
These metrics work best as a dashboard that is reviewed monthly. You do not need sophisticated BI tooling — a spreadsheet updated from ERP exports is fine to start with. The goal is consistency: the same definitions measured the same way each month, so trends are visible.
Before go-live, record the baseline for each metric. After go-live, track monthly. After six months, do a structured review: where did the numbers move as expected, where did they not, and what does that tell you about what still needs attention in the implementation?
The AP automation overview and the approval workflow post cover the process design side. The metrics above are how you verify whether that design is working in practice.