CPIM Demand Management 2 — Questions and Answers
Question 1: A company notices its forecast error consistently underestimates actual demand. This systematic bias is best corrected by:
- Increasing the smoothing constant in exponential smoothing
- Applying a positive bias adjustment to future forecasts (Correct answer)
- Switching to a qualitative forecasting method
- Reducing the forecast horizon
Correct answer: Applying a positive bias adjustment to future forecasts
Systematic bias (consistent under- or over-forecasting) should be corrected with a bias adjustment rather than changing the smoothing method.
Question 2: Which demand pattern is characterized by a regular, repeating fluctuation tied to the calendar?
- Trend
- Seasonality (Correct answer)
- Cyclicality
- Random variation
Correct answer: Seasonality
Seasonality refers to repeating demand patterns tied to specific calendar periods such as months, quarters, or seasons.
Question 3: In collaborative planning, forecasting, and replenishment (CPFR), trading partners share:
- Only historical shipment data
- Sales forecasts, promotional plans, and order information (Correct answer)
- Confidential supplier cost structures
- Internal production schedules exclusively
Correct answer: Sales forecasts, promotional plans, and order information
CPFR involves sharing forecasts, promotional plans, and order data between retailers and suppliers to align supply and demand planning.
Question 4: A demand filter is used in forecasting systems primarily to:
- Automatically adjust safety stock levels
- Flag demand data points that fall outside expected ranges for review (Correct answer)
- Calculate the optimal reorder point
- Determine customer priority rankings
Correct answer: Flag demand data points that fall outside expected ranges for review
Demand filters identify unusual demand observations (outliers) that may distort the forecast and flag them for analyst review.
Question 5: Which measure expresses forecast accuracy as a percentage of actual demand, making it useful for comparing accuracy across products with different volumes?
- Mean Absolute Deviation (MAD)
- Mean Squared Error (MSE)
- Mean Absolute Percent Error (MAPE) (Correct answer)
- Tracking signal
Correct answer: Mean Absolute Percent Error (MAPE)
MAPE expresses the error as a percentage of actual demand, enabling fair comparison across items with vastly different demand volumes.
Question 6: The 'bullwhip effect' in demand management refers to:
- Shrinking order variability as orders move upstream in the supply chain
- Amplifying order variability as orders move upstream in the supply chain (Correct answer)
- A method for smoothing seasonal demand patterns
- A technique for reducing forecast bias
Correct answer: Amplifying order variability as orders move upstream in the supply chain
The bullwhip effect describes how small demand variability at the retail level gets amplified into large swings in orders further up the supply chain.
Question 7: When a company uses point-of-sale (POS) data shared by retailers to update its forecasts, this practice is known as:
- Demand sensing (Correct answer)
- Vendor-managed inventory
- Consignment stocking
- Safety stock optimization
Correct answer: Demand sensing
Demand sensing uses real-time or near-real-time POS and consumption data to create short-horizon forecasts that are more accurate than traditional methods.
CPIM Demand Management 2
A company notices its forecast error consistently underestimates actual demand.
This systematic bias is best corrected by: