The highest degree of bias and error occurs when forecasting reports to sales, which is responsible for volume. The second-highest is when the discipline is controlled by marketing, which oversees growth and market share. The third is when the target is manufacturing. The ideal home for forecasting, says Cecere, is a profit-center manager, finance or corporate strategy function - "someone looking across the corporation, not just at vertical silos."
Unfortunately, that kind of setup is more the exception than the rule in organizations today. Over time, Cecere says, companies have "gotten a bit sloppy about the design of the supply chain."
It's tough to wrest control of the forecast from sales, she acknowledges. One reason is that sales has a natural bias for error, often based on an incentive structure. In a recession, however, it's more important than ever for companies to be "market-driven," sensitive to what's really going on among the customer base. The latency of critical data can be as high as two or three months, making it difficult for companies to respond to true market conditions.
Businesses need to take a close look at system bias and error. "Supply chains with high error should be designed for agility and responsiveness," Cecere says. "Those with low error should design for efficiency." Accurate forecasts should be encouraged and rewarded, in the form of better prices for customers. At the same time, the company needs to take responsibility for improving the forecast it conveys to upstream contract manufacturers.
"Forecast accuracy is one of the largest waste areas of the supply chain," Cecere says. In the wake of the recession, "we're now seeing people looking at accuracy as a determinant of good relationships."
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