I recently toured a Xerox service parts distribution center outside of Chicago, Illinois. During the tour I spent nearly an hour observing the order picking operation. In that operation, order pickers are each assigned to a zone of two long aisles of bin shelving. Orders are progressively assembled by conveying an order tote from zone to zone.
I especially enjoyed meeting the top-performing order picker. She had been with Xerox for over 20 years and had worked the same two aisles in the warehouse for over three years. The housekeeping, productivity, and accuracy in her zone were the highest in the warehouse. Her pride in her job was also evident by the near-perfect arrangement of the merchandise in her zone. I could not help but comment to her about the excellent performance record she had and on the neatness of her work area.
During the conversation I noticed that the merchandise in the bin closest to the front of her zone and next to the takeaway conveyor was not nearly as neatly arranged as the other bins. It was so unusual compared to other bins in her zone that we asked her about the arrangement of that particular bin. She told me the bin contained merchandise that customers were going to order that day. How did she know that? She did not have ESP or claim to function as the world’s greatest forecasting system.
The items in that bin were A-movers that had not been properly re-slotted. The order picker grew tired of traveling to the end of her zone for those popular items. She simply moved some of the inventory for those items close to the front of the zone. It would have been much better had a good AI-based slotting and re-slotting system been in place, but in the absence of that, this simple process improvement would have been impossible without the product and location familiarity that comes with operator dedicated zone picking.
True Value Hardware
At True Value Hardware, each of its small-item order picking areas is configured in single-aisle zones. A takeaway belt conveyor runs down the center of each zone, allowing an operator to make one pass through the zone during a pick wave. During a pass, each operator works with a roll of picking labels. The labels present items in location sequence to the order picker, who picks an item, places a bar code label on the item, places the labeled item on the belt conveyor, and moves to the next location. The takeaway belt conveyor feeds a downstream sortation system that sorts the items coming from each zone into retail store orders.
At the end of each zone, the performance statistics including picking productivity, picking accuracy (via internal audit), and housekeeping for the zone are posted. Talk about public accountability!
The benefits of zone picking—reduced travel time, minimal congestion, product-location familiarity, and operator-zone accountability—may or may not pay for the associated costs and inherent control complexities presented by zone picking. That's an optimization and simulation that needs to run to consider the full range of order picking concept designs.
Interesting read! Warehouse optimization is indeed crucial for efficient order picking. Leveraging product familiarity can streamline processes and reduce errors, enhancing overall performance. The article provides valuable insights into the advantages of this approach.
Great post!
Thank you for writing this post