Two key technological developments that have enabled customers to transfer and vendors to process consumption data are Electronic Data Interchange (EDI) and high-speed, batch-processing forecasting software. Coincident with the advent of these innovations was the evolution of cooperative customer-vendor business programs including Vendor Managed Inventory (VMI),
Continuous Replenishment Planning (CRP), and Collaborative Planning, Forecasting and Replenishment (CPFAR) which became the hallmarks of 1990s supply chain management. The combination of new information technology and cooperative supply chain partnerships has made possible the sharing of consumption-based forecasting information in near real time. The results of these developments have been dramatic: improvements in product-forecast accuracy, reductions in supply chain inventories, and efficiencies in product distribution.
Instead of monthly factory shipment information, vendors have begun to use four other types of demand data to drive demand planning systems. These alternative data streams are (1) customer forecasts, (2) consumer purchases, (3) customer warehouse withdrawals, and (4) customer orders. Collectively, these customer-supplied data can be used to form the basis for bottom-up product forecasts which, when aggregated and rolled back up the supply chain, more accurately predict independent demand than do factory shipment-based forecasts.
Independent demand is the requirement for items that is influenced by factors that are external to the firms that comprise the supply chain. These external factors bring about random variation in demand for such items. Consequently, independent demand forecasts are typically projections of historical demand patterns. As such, it is assumed here that independent demand is derived from point-of-sale (POS) based consumption data, since consumption is outside of the control of suppliers, vendors, and retail customers.