Automated Forecasting & Replenishment
Mastering the inventory – demand balancing act
Balancing in-store inventory levels with forecasted demand based on in-store stock levels, sales trends, seasonality and promotions is no easy task. Get it wrong and you lose revenue or need costly markdowns. But if you can get it right, you’ll see significant sales lift, improved customer satisfaction and loyalty, and reduced costs. Fortunately it’s easy to get it right with RedPrairie’s Automated Forecasting & Replenishment.
Keeping shelves stocked
Store-level demand-based forecasting ensures localized assortments are in stock in the right stores
The keys to getting forecasting and replenishment right are timely store-level data and sophisticated forecasting algorithms. It starts with POS data from each store to define demand on a localized basis. This raw data is filtered for special events and other anomalies to create a normalized demand stream which is combined with in-store inventory levels, merchandising plans such as promotions and new product introductions, and seasonal factors to create the base forecast.
The system then automatically selects from among a variety of sophisticated regression and time-series forecasting and replenishment algorithms to smooth the forecast, compare it to in-store receipts, in-transit inventory, and reorder trigger points and computes store by store replenishment needs. The result is improved localized assortments while reducing stock-outs and over-stocks. Which means higher revenue, better price performance, and reduced costs – not a bad balancing act!