How much of your direct labor hours are being eaten up by unnecessary selection travel?

Pick List Size – The Silent Productivity Killer

The first installment of our series on Data-Driven Efficiency Improvement will focus on the importance of evaluating pick list size.

Pick lists accurately reflect the number of assignments traveling through each pick line and are heavily influenced by the number of selection zones or hard breaks in the warehouse and, unlike order size, pick list size can be controlled to suit the operation. 

Pick list size is often underestimated as a performance indicator but combined with pick line length, it’s critical when it comes to minimizing selection travel and partial pallet consolidation labor at the dock.

Whether the operation is retail or wholesale, seasonality and SKU proliferation tends to wreak havoc on hard pick breaks over time and, without the proper analysis, it can go unnoticed.

The example picklist size analysis (taken from a case study we compiled of one of the leading grocery retailers in the United States) illustrated above breaks down picklist count by cube size bracket and, for the sake of this example, we’re going to consider 75 cube to be a full pallet. 

Even if we assume 60 cube to be a full pallet, only 35% of pick lists generated have enough items to make up a full pallet. Furthermore, although 28% of those pick lists are coming in over 75 cube, the second pallet is coming out at only 42 cube.

Let’s focus on the biggest take-away.

64% of pick lists generated are coming out under 59 cube with the majority being closer to a half pallet. Nearly a third of those are coming in at only 6 cube.

What are the productivity implications? For the purpose of keeping it simple, let’s consider a imaginary warehouse layout with 6 aisles (100 linear feet each) of conventional racking with no tunnels. This means that an average order selector is traveling 2 full aisle lengths (200 linear feet) from start to finish, at minimum, per pick list, regardless of where the picklist physically begins and ends.

Using our example, that means that, for 64% of pick lists, at least 200 linear feet is being traveled for an average of 33 cube or less.

If travel distance cannot be minimized, productivity must be maximized by having selectors stay busy while they travel.

Not only do large, versatile, pick breaks help you to utilize the full length of each aisle, minimizing unnecessary travel, they also help with the following:

1.   Increase pick list size – and hit rate, if pick breaks are planned and maintained properly.

2.   Allow for slot optimization, as more material handling options are typically available.

3.   Minimize consolidation at the dock due to partial pallets coming out of each pick break.

The bottom line is that, unless the tools are available to monitor this continuously throughout the year, this metric – and its impact on productivity and cost per case – can be easily missed.

Trust your data and make more informed decisions.

Stay tuned for the next installment of our series on Data-Driven Efficiency Improvement. It will focus on another critical, yet underestimated, productivity metric:  pallet configuration.