MAPE is the most widely used forecast accuracy metric because it's easy to explain. Planners typically measure it at the SKU or SKU-location level over a fixed lag, such as the forecast made three months before the period. The lag matters: accuracy one week out is always better than three months out.
MAPE has known weaknesses. It divides by actuals, so slow movers with tiny volumes can show huge percentage errors that distort the average, and it's undefined when actual demand is zero. Weighted MAPE (WMAPE) fixes this by weighting errors by volume, which is why many planning teams report both.
In software: demand planning tools such as Kinaxis, o9 and Netstock report MAPE and WMAPE alongside bias, so teams can track accuracy by product family, region and forecast lag.
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