Plain-language questions
Ask for picking accuracy per month, customer or product in the SQL Explorer with AI. The AI writes the SQL, you see the query and run it yourself; the AI only receives metadata.
KPI · Logistics
Picking accuracy is the percentage of order lines picked without an error: the right item in the right quantity. A picking error almost always leads to extra cost, such as a return, a reshipment or a complaint. That makes it a core KPI for warehouse quality.
(Order lines picked − lines with an error) ÷ order lines picked × 100%
In May 2026 Acme Groothandel's warehouse picked 48,000 order lines. 144 errors were found. Picking accuracy is (48,000 − 144) ÷ 48,000 × 100% = 99.7%.
Fictitious figures for Acme Groothandel, a sample wholesaler.
Higher picking accuracy means fewer returns, reshipments and complaints. Because the percentages tend to sit close together, errors per 1,000 lines is sometimes easier to read. Compare by zone, product group and picking method with your own earlier periods, and look at which type of error is most common.
SQL & DAX
Two examples on a fictitious data warehouse for Acme Groothandel: a PostgreSQL query and a measure for a Power BI model. Adjust table and column names to your own model.
SELECT date_trunc('month', picked_at) AS month,
SUM(lines) AS lines_picked,
SUM(errors) AS pick_errors,
ROUND(100.0 * (SUM(lines) - SUM(errors)) / NULLIF(SUM(lines), 0), 2) AS picking_accuracy_pct
FROM picks
GROUP BY 1
ORDER BY 1;Lines Picked = SUM(Picks[Lines])
Picking Accuracy = DIVIDE([Lines Picked] - SUM(Picks[Errors]), [Lines Picked])In ENABLE
Ask for picking accuracy per month, customer or product in the SQL Explorer with AI. The AI writes the SQL, you see the query and run it yourself; the AI only receives metadata.
Define the KPI as a measure in your Power BI model and show it in the portal, with "Last refreshed" next to it. Access profiles and optional row-level security decide who sees which figures.
Add the KPI as a tile to a custom dashboard, compared with last year. The Dashboard Builder is a pilot and can be switched on per client.
With the built-in Targets app you set a target for the KPI per month, so you see actuals and target side by side.
FAQ
Subtract the number of order lines with an error from the total lines picked and divide by that total. An error is a wrong item, a wrong quantity or a damaged item that was packed anyway. Combine errors from your own checks with those reported by customers.
The most common are a wrong item, a wrong quantity, a missing item and the wrong variant, such as size or colour. Record the type with every error. That tells you whether to look for the cause in locations, labelling or the picking method.
Scanning during picking is usually the biggest improvement, because it stops wrong items straight away. Clear locations, keeping look-alike items apart and a check at packing also help. Measure after each change whether errors per 1,000 lines go down.
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