Abstract
Seasonal demand for products is common at many companies including Kraft Foods, Case New Holland, and Elmer’s Products. Planning inventory and production in the face of seasonal demand can be challenging. Many companies experience a severe drop in inventory and service as they transition from a high season to a low season. Kraft has termed this phenomenon the 'landslide effect.' In this paper, we present real examples of the landslide effect and describe its causes by comparing common industry practice to the correct inventory mathematics for non stationary demand. We investigate the magnitude and drivers of the landslide effect through both an analytical model and a case study. We find that the effect increases with seasonality, lead time, and demand uncertainty and can lower service by an average of ten points at a representative company. Companies can avoid the landslide effect by using demand forecasts over the preceding lead time to calculate safety stock targets.
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