In retail, the supplier often takes most of the demand risk. The retailer wants accurate forecasts to reduce inventory carrying costs and improve yields, but they don't have the same level of skin in the game that suppliers do, if demand doesn't materialize. The supplier usually is the one who has to pay for markdowns, spoilage, returns, and junking. Suppliers can successfully fill every customer order and still "lose their shirt." Predicting demand based on orders from the retailer is challenging, because the order stream is filled with noise: forward buy distortions, buyers tinkering, order-type errors (marked as a promotion when it's really a reorder), one-time shipments, etc. In addition, the order rates are sporadic, not a continuous flow.
So suppliers need to stop asking what will our customer order and start asking what should our customer order to meet end consumer demand. They should change their goal from high fill rates only, to having high fill rates, high store-level in-stocks, and high sell-through. Most current systems and approaches struggle to meet these goals. They rely too heavily on retailers' forecasts, because they don't have a structured approach to intelligently incorporate POS data or the true impact of recent orders.
