CDPP Demand Planning Metrics & Performance Management

Question 1

What does MAPE stand for in demand planning?

Accepted Answer

Mean Absolute Percentage Error

Answer

MAPE (Mean Absolute Percentage Error) measures forecast accuracy as the average absolute percentage difference between forecasted and actual demand.

Question 2

What is a key limitation of MAPE as a forecast accuracy metric?

Accepted Answer

It becomes undefined or skewed when actual demand is zero or very low

Answer

MAPE divides by actual values, so when actuals are zero or near-zero the metric becomes undefined or extremely large, distorting the overall accuracy picture.

Question 3

What does forecast bias indicate in demand planning?

Accepted Answer

A systematic tendency for forecasts to be consistently too high or too low

Answer

Forecast bias reveals a directional pattern in forecast errors—consistently over-forecasting leads to excess inventory while consistent under-forecasting causes stockouts.

Question 4

How is Mean Error (ME) used to detect forecast bias?

Accepted Answer

A positive ME indicates consistent over-forecasting; a negative ME indicates consistent under-forecasting

Answer

Mean Error averages signed forecast errors (forecast minus actual), so positive values reveal systematic over-forecasting and negative values reveal under-forecasting.

Question 5

What is the primary difference between MAD and RMSE as forecast error metrics?

Accepted Answer

RMSE penalizes large errors more heavily due to squaring, while MAD treats all errors equally

Answer

Because RMSE squares errors before averaging, large individual errors receive disproportionately higher weight compared to MAD, making RMSE more sensitive to outliers.

CDPP - Certified Demand Planning Professional Practice Test

CDPP - Certified Demand Planning Professional Practice Test

CDPP Demand Planning Metrics & Performance Management