SYSTEM AND METHOD FOR STORE LEVEL LABOR DEMAND FORECASTING FOR LARGE RETAIL CHAIN STORES

摘要

A system and method for store level labor demand forecasting for large retail chain stores are disclosed. In one embodiment, a chain store level labor budget in labor hours for a future point-in-time is determined. Further, backend labor hours are obtained for each store using a backend regression equation that is based on forecasted independent variables. Furthermore, frontend labor hours are obtained for each store using a frontend regression equation that is based on customer service driven factors and using a what if scenario model to select best case values of the customer service driven factors. In addition, needed store level labor hours are obtained for each store by aggregating the obtained backend and frontend labor hours. Moreover, store peer groups are formed and a performance rank of each store within each store peer group is obtained. Also, allocated chain store level labor hours to each store are optimized. [FIG. 4]