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Next Generation Demand Management by Charles W. Chase

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Chapter 5Performance Metrics

Measuring forecast performance is one of the most important elements of the demand forecasting process, and the least understood when put into practice. As you know, what gets measured gets fixed, and what gets fixed gets rewarded. You cannot improve your forecast accuracy until you measure and benchmark your current forecast performance.

It is not unusual to encounter companies that have never truly measured the accuracy of their demand forecasts on an ongoing basis. Some measure forecast accuracy weekly, monthly, and quarterly at the most aggregate level in their product hierarchy with little focus on the lower levels—the stock-keeping unit (SKU) detail or internal mix within the aggregates. It is not uncommon to find many companies that have virtually no idea that their lower-level product forecasts at the brand, product group, and the SKU detail have extremely high forecast error (or very low forecast accuracy). This is usually attributed to the way they calculate forecast accuracy (or error). They normally do not measure forecast error in terms of absolute values. As a result, when they sum those error values to the aggregate levels, the plus and minus signs wash each other out, making the accuracy look much better than the lower level detail. In fact, most senior-level managers rarely use or understand the term forecast error. The burden of translating forecast error to more understandable forecast accuracy terms normally falls on the shoulders ...

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