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In the past decade, companies have invested billions in Quick Response, JIT, Flexible Manufacturing, and similar initiatives. The reason given for these investments has usually been to improve customer service, that is, to respond faster to customers' changing demands.1 Many of these companies could have achieved the same competitive results in a much less costly way, namely, better forecast­ing. Whenever companies can better anticipate what their customers will want and when, their savings in smoother operations and customer satisfaction far outweigh any added costs in forecasting. Indeed, the economics of better forecasting are so lopsided they invite the question, Why don't companies give more attention to improving this function, with or without JIT, Quick Response, and the like?

The simple answer is they probably would if they thought they could. But many business executives are skeptical, if not downright cynical, about the reliability of demand forecasts. Frustrated by unsuccessful improvement ef­forts, they have given up hope of better forecasting and turned to other, more costly avenues for staying competitive.

In many companies, the forecasting function today is in about the same condition as the quality function was before 1980. There is no corporate focus on the subject. Individual units are left to generate, and use, forecasts in whatever ways they wish. Forecasters are often viewed as isolated specialists, and their work is ignored or overridden by operating managers. Relevant information is not well snared among departments, if at all.

When managements do focus on improving this function, the results can be dramatic. Perhaps the best-known examples, in our service economy, are the airlines and some hotel companies, which have turned forecasting, pricing, and capacity utilization into a science, based on extensive analyses of demand. Similar, but less publicized, examples exist in manufacturing, retailing, and other industries.

Gauging Your Opportunities

A weak or unreliable forecasting process often displays certain telltale signs. Here are some common examples:

• After detailed preparation of forecasts by the operat­ing units, top management injects large "adjustments" based on gut feel.
• Forecasts are over-influenced by those who can talk the loudest (or the longest).
• Your company reacts to market "signals" you know to be unreliable.
• There is little if any contingency planning.
• Lost demand isn't measured or factored into the ensu­ing forecasts.
• People privately bypass the forecasts and build secret cushions into their numbers.
• "Top-down" and "bottom-up" forecasts are never recon­ciled (or one is missing).
• There is no established procedure for reviewing the accuracy of past forecasts.
• Different groups in the company forecast based on conflicting assumptions and data.
• Drivers of demand are not understood.

If these signs or similar ones sound familiar, your company's forecasting processes are probably a good candidate for improvement or reengineering. Other factors that increase your potential gain from better forecasting include perish­able products, high numbers of SKUs in your product line, a significant fraction of new products every year, a high degree of seasonality in your sales, and a high reliance on repeat customers (and therefore a high importance to customer service levels).

To be Continued