Forecast Accuracy Metrics
Forecast Accuracy Metrics We will be discussing here about the most commonly used forecast accuracy metrics mentioned below: Forecast bias MAD MAPE MSE RMSE MPE Forecast Bias This metric will help us in understanding whether the model has over estimated or under estimated. If the value is positive then its overestimation and if its negative then underestimation. In order to get bias as a % of sales, we have Forecast Bias % fig: relexsoumtions If the value is more than 100 % then its an over forecast and if its less than 100% its under forecast. It is important metric in demand forecasting as it will tell us the over or under supply at the central warehouse or distribution centers. It does not give information on quality of detailed level of forecast. Target is to achieve a 1 or 100% and the number -/+ tells the deviation. 2. Mean Absolute Deviation (MAD) This metrics