Which metric expresses forecast error as a percentage of actual demand?

Which metric expresses forecast error as a percentage of actual demand?

• A. MAPE
• B. MAE
• C. RMSE
• D. MFE

Answer: (A)

MAPE expresses forecast error as a percentage of actual demand. It takes the absolute difference between what was observed and what was forecast, divides that by the actual demand for each period, and then averages these percentages. This standardizes errors so you can compare performance across items and time periods with different demand levels. For example, a 10-unit error is 10% when actual is 100, but 50% when actual is 20, highlighting the relative impact of the same absolute error. The other metrics measure error in different ways: MAE uses units of demand, RMSE emphasizes larger errors by squaring, and MFE shows bias through signed errors. Be aware that MAPE can be problematic when actual demand is very small or zero, but it’s the typical choice when you want a percent-based accuracy measure.

MAPE expresses forecast error as a percentage of actual demand. It takes the absolute difference between what was observed and what was forecast, divides that by the actual demand for each period, and then averages these percentages. This standardizes errors so you can compare performance across items and time periods with different demand levels. For example, a 10-unit error is 10% when actual is 100, but 50% when actual is 20, highlighting the relative impact of the same absolute error. The other metrics measure error in different ways: MAE uses units of demand, RMSE emphasizes larger errors by squaring, and MFE shows bias through signed errors. Be aware that MAPE can be problematic when actual demand is very small or zero, but it’s the typical choice when you want a percent-based accuracy measure.