As MAPE is a calculation of errors, a high percentage means bad, and a low percentage means good. As there is no weighting on quantities or on values, periods of high demand can easily be underestimated with this method. Read More: How to Forecast in Excel Based on Historical Data Method...
In Microsoft Dynamics AX 2012 R3, forecast accuracy is measured by using these key performance indicators: mean absolute deviation (MAD) and mean absolute percentage error (MAPE).When you calculate forecast accuracy you define the period during which historical data is collected. You can also ...
In Microsoft Dynamics AX 2012 R3, forecast accuracy is measured by using these key performance indicators: mean absolute deviation (MAD) and mean absolute percentage error (MAPE).When you calculate forecast accuracy you define the period during which historical data is collected. You can also ...
In Microsoft Dynamics AX 2012 R3, forecast accuracy is measured by using these key performance indicators: mean absolute deviation (MAD) and mean absolute percentage error (MAPE).When you calculate forecast accuracy you define the period during which historical data is collected. You can also ...