How to avoid data entry errors in accounts payable (what the research says)

A mistyped invoice is never just a typo. In accounts payable, a transposed figure, a wrong vendor match or an invoice entered twice quickly turns into a duplicate payment, a missed discount or hours of cleanup. And contrary to a stubborn belief, the problem is not that your clerks lack rigour: manual data entry is error-prone by nature. Research has shown it for years, and the good news is that these errors are among the easiest to eliminate.

What the research says about manual data entry

Serious studies on human error all point to the same thing: the moment a human re-keys data, a share of errors creeps in, no matter how careful the person is.

In other words: across hundreds of invoices a month, an error rate of "only" 1 to 2% mathematically guarantees that mistakes slip through. The real lever is not pushing teams to be "more careful," but taking manual entry out of the equation.

Why it costs so much in accounts payable

A data entry error does not just cost the fix. It ties up time: the McKinsey Global Institute estimates that administrative employees spend nearly 19% of their week searching for and gathering information. Every invoice that has to be found, corrected or matched by hand eats into that capacity. Add duplicate payments, discounts lost for lack of timely processing, and vendor follow-ups, and the bill adds up fast.

How to actually avoid data entry errors

Data entry errors are among the easiest problems to automate, because they are repetitive and measurable. Four concrete levers:

1. Capture instead of keying. OCR extracts the text from the invoice (vendor, amounts, taxes, number) and AI contextualizes it; the fields pre-fill. No one re-types.
2. Match automatically (three-way). The software compares purchase order, invoice and receipt. A mismatch in amount or quantity is flagged before payment, not after.
3. Catch duplicates upstream. The same invoice received by email and by mail is detected automatically, before it is paid twice.
4. Validate by exception. People only handle the doubtful cases, with a signed audit trail, instead of re-keying everything.

The research lesson: verify, do not re-read

The same work by Barchard and Pace adds a valuable nuance: double entry, which means keying the value twice and then comparing the two versions, drops the error rate to about 0.03%, roughly thirty times lower than single entry. Plain visual re-reading, by contrast, is far less effective. The lesson is counter-intuitive: you do not fix data entry errors by re-reading more carefully, but by having the data checked by a second mechanism. Automation applies exactly that logic. The software reads the invoice, then checks it against the purchase order and history: a permanent double check, without the workload of manual double entry.

In short

The research is clear: as long as a human keys invoices by hand, an irreducible error rate remains. The answer is not vigilance, it is automating capture, matching and duplicate detection. That is exactly what proprietary accounts payable software, built and hosted in Canada, is designed to do.

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Frequently asked questions

Sources

• Barchard, K. A., & Pace, L. A. (2011). Preventing human error: The impact of data entry methods on data accuracy and statistical results. Computers in Human Behavior, 27(5), 1834-1839. Abstract (DOI 10.1016/j.chb.2011.04.004)
• Panko, R. R. Research on human error and data entry error rates. arXiv:0801.3114
• McKinsey Global Institute (2012). The social economy: Unlocking value and productivity through social technologies. Report