Certified Supply Chain Professional CSCP Practice Certified Supply Chain Professional (CSCP) Demand Management and Forecasting 1

Question 1

Which forecast error metric expresses accuracy as a percentage of actual demand, making it useful for comparing performance across products with different scales?

Accepted Answer

Mean Absolute Percentage Error (MAPE)

Answer

MAPE expresses the average forecast error as a percentage of actual demand, which normalizes the measure and allows meaningful comparison across SKUs or product lines that have vastly different demand volumes.

Question 2

A supply chain manager observes that orders placed by retailers are far more variable than actual consumer demand at point of sale. This phenomenon is best described as:

Accepted Answer

The bullwhip effect

Answer

The bullwhip effect describes how demand variability amplifies as it moves upstream through the supply chain, so small fluctuations at the consumer level become large swings in retailer and distributor orders.

Question 3

In exponential smoothing, a higher smoothing constant (alpha) value results in:

Accepted Answer

A forecast that responds more quickly to recent demand changes

Answer

A higher alpha gives more weight to the most recent actual demand observation, making the forecast more responsive to recent changes. A lower alpha smooths more by weighting historical data more heavily.

Question 4

Collaborative Planning, Forecasting, and Replenishment (CPFR) is primarily designed to:

Accepted Answer

Reduce forecast error by sharing information between trading partners

Answer

CPFR is a business practice where retailers and suppliers share sales data, promotional plans, and forecasts to create a single agreed-upon demand plan, reducing the information asymmetry that causes forecast errors.

Question 5

When calculating safety stock, which two factors are most directly used to determine the appropriate buffer level?

Accepted Answer

Lead time variability and forecast error (demand variability)

Answer

Safety stock is mathematically driven by demand variability (forecast error) and lead time variability. Together they determine how much buffer inventory is needed to maintain a target service level despite uncertainty.

Certified Supply Chain Professional CSCP Practice Practice Test

Certified Supply Chain Professional CSCP Practice Practice Test

Certified Supply Chain Professional CSCP Practice Certified Supply Chain Professional (CSCP) Demand Management and Forecasting 1