Optimization of Retail Disposition

Challenge

Optimizing product disposition in warehouses is a complex issue often shaped by manual work or experience-based insights. An automatic disposition system helps retailers avoid out-of-stock situations that can occur due to human factors. Our client, an international retail company, faced the challenge of optimizing their existing disposition engine during the Christmas season to prevent excessive automatic reorders after December 24th. Such overorders were previously generated by the client's automated engine, which calculated quantities to order based on short-term historical data.

Approach

After a detailed examination of sales and inventory data, we tested and compared various methods to develop a model that automatically adjusts the forecasts of the disposition engine according to seasonal patterns and the Christmas period. It uses the patterns from previous Christmas periods to extrapolate into the future, thus avoiding unnecessary orders after Christmas.

Result

The integration of statistical methods into the existing engine automatically corrected overordering during the Christmas season. After implementing the engine correction, both out-of-stock and overstock situations during the Christmas period were successfully avoided, along with massive reorders.