CDPP Demand Planning Metrics & Performance Management

Question 1

What does MAPE stand for in demand planning?

Accepted Answer

Mean Absolute Percentage Error

Answer

Monthly Average Planning Estimate

Answer

Moving Average Projection Error

Answer

Maximum Allowable Planning Error

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

It cannot be calculated for monthly data

Answer

It measures bias rather than accuracy

Answer

It requires normally distributed demand data

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

Random variation in the forecast

Answer

The spread of errors around the mean

Answer

The accuracy of seasonal adjustments

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

It measures the absolute size of each error

Answer

It measures the variance of the forecast errors

Answer

It calculates the percentage error for each period

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

MAD is only used for seasonal products; RMSE for non-seasonal

Answer

MAD requires normally distributed data; RMSE does not

Answer

RMSE is a percentage measure; MAD is an absolute measure

Question 6

What is a typical 'best-in-class' MAPE benchmark for fast-moving consumer goods (FMCG) demand planning?

Accepted Answer

Less than 20%

Answer

Less than 5%

Answer

Less than 50%

Answer

Less than 80%