Stanford Professor Hau Lee, who heads up the Stanford Global Supply Chain Management Forum, says manufacturers have been trying to solve demand forecasting for as long as there have been factories. Newer technologies, particularly Internet-based collaboration systems that allow manufacturers, suppliers and customers to work together on new products and jointly form market forecasts, have gone a long way toward improving the accuracy of demand planning. However, Lee says, many other business factors, cultural issues and the inevitable unexpected event will always make forecasting a daunting job. "The technologies we have today help us do a much better job than we ever could before, but sometimes the wheel still falls off the wagon," he says.
Lee points to two critical areas that have plagued companies over the years. First, much of the data people use to develop their forecasts is "polluted," contaminated by special events that happen in the marketplace that can't be easily recognized, or that are utterly unprecedented, such as the events of Sept. 11. But while technology can't tell what is going on in the mind of the customer, it can recognize anomalies in sales patterns, which in turn should cause manufacturers to investigate further before ramping up production. Second is the lack of a feedback mechanism. "People make forecasts, and they know their forecasts will always be wrong to a certain degree, but they don't have the means to learn from it," he says.
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