WMS, Warehouse Labor & Fulfillment worked example

Pick Accuracy at 99% target pick accuracy rate: a worked example

What does the result look like when target pick accuracy rate reaches 99%? The full calculation is worked below with real intermediate numbers. Use it when pick accuracy in wms, warehouse labor and fulfillment needs a clean rate and gap-to-target you can put on a tier board.

The inputs for this scenario

Accurate Picks Verified: 8 count (unchanged)
Total Picks Audited: 250 count (unchanged)
Target Pick Accuracy Rate: 99 % (raised for this scenario; the documented default is 95)

Working through the calculation

Applying the documented formula (Pick accuracy rate = pick accuracy count ÷ total pick accuracy population × 100) to the inputs above produces each figure below.
At this operating point the engine returns 3.2 % for pick accuracy rate, the number this scenario is built around.
At this operating point the engine returns 95.8 points for pick accuracy gap to target.
At this operating point the engine returns 8 count for pick accuracy count.
At this operating point the engine returns 250 count for total pick accuracy population.

How this compares with the baseline

Against the tool's baseline example, where target pick accuracy rate sits at 95% and the headline result is 3.2 %, this scenario lands almost exactly on the baseline at 3.2 %.
A figure at this level is achievable when target pick accuracy rate is genuinely sustained, not just peaked for a shift. Accuracy depends entirely on the audit sample, so a small or biased sample can misstate true performance; audit enough picks across pickers and zones to be representative.

Results at a glance

Pick accuracy rate: 3.2 % (headline result)
Pick accuracy gap to target: 95.8 points
Pick accuracy count: 8 count
Total pick accuracy population: 250 count

Run it with your numbers

Every input above is editable in the live Pick Accuracy calculator, which recalculates instantly and can be shared with the inputs intact.

Last reviewed 2026-05-12.