Top-Down Versus Bottom-Up Demand Forecasts: The Value of Shared Point-of-Sale Data in the Retail Supply Chain
基于美国18个区域配送中心10种即食麦片的周销售点数据和订单数据，研究自上而下与自下而上两种需求预测方法的准确性，以及共享销售点数据能否提升预测精度。
Accurate demand forecasts are critical to maintaining customer service levels and minimizing total costs, yet increasingly difficult to achieve. Using weekly point-of-sale (POS) and order data for 10 ready-to-eat cereal stock-keeping units from 18 regional U.S. grocery distribution centers, this research empirically investigates two demand forecasting issues: (1) the accuracy of top-down versus bottom-up demand forecasts; and (2) whether shared POS data improve demand forecast accuracy. The results reveal a previously unexplored relationship between demand forecast methodology and the use of shared POS data. We find that the superiority of the top-down or bottom-up forecasting as the more accurate demand forecast method depends on whether shared POS data are used.