Pick Rate

Pick rate is the number most operations managers reach for first when building a business case for warehouse automation. It's easily measurable, comparable across facilities and is a metric that is directly tied to a labour cost. Get the before and after figures right and the ROI calculation becomes concrete and easy to present.

The metric captures something specific, the impact of walking, the impact of travelling between pick locations. In a manual warehouse, a meaningful proportion of each picker's hour is spent moving between pick locations rather than picking product. Goods-to-person eliminates that travel, which is why the productivity uplift can look dramatic, it's not that picking itself gets faster, it's that the non-productive time disappears.

Pick rate has real limits as a standalone metric. A high pick rate with a high error rate isn't a win. Pick accuracy, the percentage of picks that are correct first time, should always be tracked alongside it. Some GTP and ASRS systems improve both simultaneously, which strengthens the ROI case further.

Pick rate = total picks completed divided by total hours worked, it's a simple calculation so long as you have the data. Tracking it accurately requires a WMS or equivalent system that timestamps each scan event. Manual counting isn't viable at any meaningful scale.

When comparing pick rates across facilities or evaluating vendor claims, check the definition of a 'pick.' Some vendors count by order line, some by item, some by unit. These aren't the same in operations where a single pick might be multiple units of the same SKU.

For ROI modelling, the relevant figure is picks per paid hour, not picks per active-pick minute. Paid hours include breaks, shift start and end time, training, and any non-picking tasks the operator performs during the shift. Using raw active-pick figures overstates the manual baseline and understates the true improvement from automation.