If something is not measured, it will never improve. To improve forecast performance, we must have metrics in place to measure and monitor them. There will be inherent volatility and variability in what we forecast and if there is any human judgement, there is the possibility of bias in our consensus Demand Plan.
If we can measure and recognize the error, we can do something about it. Plus, with the knowledge of the error, we will be in a better position to make better decisions as a business and manage the risk associated with it. Because of this, every step of the Demand Planning process should have two fundamental objectives:
It is clear that forecast error and bias - in either direction - can be problematic not only to a supply chain, but to the entire organization. The over-forecasting error increases cost of inventory, transshipment, shrinkage, and obsolescence. The under-forecasting error increases production, procurement and transportation costs, as well as the loss of sales because of stock-outs.
To measure and mitigate, this we use some key performance indicators for forecasting:
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