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Is Forecast Accuracy a good measure?
Many companies diligently track the accuracy of their monthly forecasts. It’s an important measure, reported and discussed at the S&OP meetings. They spend a lot of time, effort and money to improve it.
Is it a good practice to be emulated?
It makes sense for companies whose stock deployment is based on the monthly forecast. Since actual demand is often widely different from the forecast, they suffer from perennial stockouts and inventory surplus.
Companies on the agility journey, on the other hand, do not depend on monthly forecasts. Their stock deployment is based on evolving demand patterns, deciphered by Demand Sensing algorithms. They don’t need to track monthly forecast accuracy.
The first set of companies believe that inventory mismatch is due to poor forecast accuracy. Their improvement journey often stalls at this stage.
The second set of companies see the root cause as gaps in Demand Sensing, lack of flexibility in backend operations, and delayed response to demand shifts. All these are actionable. Their improvement journey never stops.
Are you still stuck in the forecast accuracy trap?