“Data analysis” is a name given to the process of evaluating and interpreting historical electronic data. In distribution environments, we most commonly look at historical product and order data, to look for patterns and opportunities that are not apparent from observation alone. This month I look at a specific type of analysis which can be done for operations that have a small number of SKUs common to many orders.
A favorite analysis of mine for small SKU environments is called “order completion analysis.” Using the analysis, we first rank the SKUs by unit movement velocity, fastest to slowest. We then take the top 10 SKUs and determine what percentage of orders can be 100% completed with just those SKUs. The same analysis is repeated for the top 20, 40, 80, etc SKUs. Recently, I performed this analysis for a client who had approximately 400 SKUs in total. We found that when looking at only the top 150 SKUs by unit movement, we could complete about 80% of their orders. The other 250 SKUs were only required for about 20% of the orders. As a result, a recommendation was made to put the 150 SKUs together in a special “fast pick” area, and this enabled the picking of 80% orders to occur much more efficiently.
A word of warning: if you do put your fast movers together, make sure that the pick system can handle the volume of pick activity. Aisles need to be big enough, and if a conveyor system is used, it must be able to handle the order volume. If not, congestion and traffic jams can occur and “elbow bumping” may become unacceptable. Order completion analysis is just one example of many analyses that can be done to enhance a picking operation. Historical data can be used to perform “what ifs?” to see which opportunities have the greatest value to the operation with a minimal labor effort, and the question can be asked before any physical changes to the operation take place. The results can provide highly objective information about the potential for operational improvement.
Sam Flanders is president of Durham, NH-based consultancy Warehouse Management Consultants.