How do you perform forecasting and replenishment for a major supermarket chain? Recently, Bobby Lane, Senior Manager of Inventory Management at Winn Dixie Stores, shared his story of moving Winn Dixie over to computer generated ordering with the SAP Forecasting and Replenishment solution at the SAP Retail Forum North America in 2012. As background, Bobby is responsible for all of the retail inventory systems in Winn Dixie stores. He serves as a liaison between store operations and IT, working closely with both parties to find IT solutions which store associates will readily embrace and use.
Before implementing SAP’s Forecasting and Replenishment solution, Winn Dixie store associates manually performed product orders based on their emotions and immediate observations, rather than based on facts. Three problematic scenarios arose from manual ordering:
- The store associate saw an empty shelf for a slow selling item. He orders a large supply of the item, because he wants the shelf to look full. However, if the item is a time-sensitive, perishable item, the store risks not being able to sell the items before they expire, thus causing a loss in profits.
- The store associate saw a full shelf for an ultra fast seller when performing manual orders. As a result, he does not order any more products. He doesn’t realize that by the time the product orders actually arrive, the ultra fast selling product may have sold out, leaving an empty shelf for days. This leads to the loss of potential profits.
- An unsupervised toddler rips off the tag for an item off the shelf. The store associate does not see a product tag and cannot remember what item was there before. He does not place a product order.
These three issues can all be easily resolved with the SAP Forecasting and Replenishment solution. F&R places computer-generated orders based on past product purchasing data and the demand period. Translation: F&R understands the difference between a slow or fast seller, and also understands if an item is time-sensitive. It does not order simply for the “here and now,” but looks at the demand horizon to understand how much to order for when the next product delivery truck will arrive. It enables the store to have the right amount of product to bridge the gap between now and when the stock gets replenished. Furthermore, with F&R, the system orders according to a plan-o-gram. Therefore, it does not matter if product tags get ripped off the shelf; the product code is in the F&R system and will get automatically re-ordered when the store needs more.
With the SAP Forecasting and Replenishment system, Winn Dixie successfully moved its stores off of a painstaking and often inaccurate manual ordering system to a computer-generated ordering process. As a result, Winn Dixie has been able to virtually eliminate almost all distribution voids in its stores!
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