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KPI · Logistics

Picks per hour: formula and example.

Picks per hour is the average number of order lines a picker or team collects per hour spent picking. It is the most widely used productivity measure in the warehouse. Together with picking accuracy it shows whether speed is coming at the expense of quality.

Picks per hour formula

Order lines picked ÷ picking hours

Worked example

In May 2026 one picker at Acme Groothandel collected 6,300 order lines in 75 picking hours. That is 6,300 ÷ 75 = 84 picks per hour.

Fictitious figures for Acme Groothandel, a sample wholesaler.

How to read this KPI

More picks per hour means lower labour cost per order, as long as picking accuracy holds up. The figure depends heavily on warehouse layout, order profile and picking method, such as single-order or batch picking. Compare within the same warehouse and zone over time, and always alongside the error rate.

Pitfalls with picks per hour

  • Comparing pickers who work in zones with very different products or walking routes.
  • Counting all hours worked instead of picking hours only, or the reverse, without recording it.
  • Pushing for speed without showing picking accuracy alongside.

SQL & DAX

Calculating picks per hour in SQL and 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.

SQL · PostgreSQL
SELECT date_trunc('week', picked_at) AS week,
       picker_id,
       SUM(lines) AS lines_picked,
       ROUND(SUM(minutes) / 60.0, 1) AS pick_hours,
       ROUND(SUM(lines) / NULLIF(SUM(minutes) / 60.0, 0), 1) AS picks_per_hour,
       ROUND(100.0 * SUM(errors) / NULLIF(SUM(lines), 0), 2) AS error_pct
FROM picks
GROUP BY 1, 2
ORDER BY 1, picks_per_hour DESC;
DAX · Power BI
Pick Hours = DIVIDE(SUM(Picks[Minutes]), 60)
Picks per Hour = DIVIDE(SUM(Picks[Lines]), [Pick Hours])

In ENABLE

Tracking this KPI in ENABLE

Plain-language questions

Ask for picks per hour 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.

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In your Power BI dashboard

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.

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Custom dashboards (pilot)

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.

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Monthly targets

With the built-in Targets app you set a target for the KPI per month, so you see actuals and target side by side.

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FAQ

Frequently asked questions

How do you calculate picks per hour?

Divide the number of order lines picked by the number of hours spent picking. Decide whether you count lines, units or orders, and whether breaks and walking between orders are included. Apply that definition consistently.

Should picks per hour count order lines or units?

Usually order lines, because each line means a visit to a location. Units per hour can be a useful addition when lines range from one unit to a hundred. Always state which unit you use.

How do you increase picks per hour?

Most picking time is spent walking, so placing fast movers close to the packing station often helps most. Batch picking, where you collect several orders in one round, shortens walking further. Keep an eye on picking accuracy at the same time.

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