Our distribution center is evaluating picking strategies to improve throughput during peak season. We’re currently using wave picking where we group orders for simultaneous picking across zones, but we’re considering switching to batch picking where a single picker handles multiple orders in one pass.
I’m interested in hearing real-world experiences with both approaches, particularly regarding mobile device scanning performance and UI responsiveness. Our warehouse team reports that the mobile app sometimes lags during batch picking when they’re scanning items for 8-10 orders simultaneously. The UI responsiveness during high-volume periods seems to vary between the two methods.
Some supervisors have mentioned noticing more scanning errors with batch picking, especially when volume is high. Has anyone compared these methods in a similar environment? What factors influenced your decision, and how did mobile device performance impact picker productivity?
I’ve implemented both methods across five facilities. The scanning error issue with batch picking is real and usually stems from two factors: UI responsiveness as you mentioned, and picker confusion when the app doesn’t clearly indicate which order the current scan applies to. We mitigated this by customizing the mobile device display to show larger order identifiers and implementing audio confirmation for each scan. The wave picking approach has fewer scanning errors because pickers focus on one order context at a time, but it requires more coordination and better wave planning to achieve similar efficiency gains.
We switched from wave to batch picking last year and saw a 20% reduction in travel time, but you’re right about the mobile device challenges. With batch picking, the mobile app has to maintain state for multiple orders simultaneously, which increases memory usage and can cause UI lag. We found that limiting batches to 6 orders max helped significantly with app responsiveness. The scanning errors you mentioned are often related to pickers losing track of which order they’re currently picking for when the UI is slow to update.
Have you considered a hybrid approach? We use wave picking for our standard orders and reserve batch picking for small orders with similar SKUs. This gives us the efficiency of batch picking where it works best while avoiding the mobile device performance issues on complex picks. The mobile app handles smaller batches much better - we cap at 5 orders per batch and only combine orders with fewer than 10 lines each. This keeps the UI responsive and reduces scanning errors to acceptable levels.
The scanning error rate difference between wave and batch picking is well-documented. In batch picking, pickers make about 15-20% more scanning errors due to the cognitive load of managing multiple order contexts. However, the overall efficiency gain from reduced travel time usually outweighs this if you can address the root causes. Invest in better picker training specifically for batch picking workflows, and ensure your mobile devices have sufficient processing power. We also found that color-coding orders on the mobile screen reduced errors by 12%.