Demand Management & Forecasting Flashcards
7 cards from real CPIM practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Demand Management & Forecasting flashcards as text
Which demand planning concept involves breaking down an aggregate forecast into individual SKU or location-level forecasts?
Answer: Demand disaggregation
Demand disaggregation splits a higher-level aggregate forecast down to granular levels such as SKU, region, or customer.
A company's product has a seasonal index of 1.3 for Q4. If the annual average monthly demand is 1,000 units, what is the expected Q4 monthly demand?
Answer: 1,300 units
A seasonal index of 1.3 means Q4 demand is 30% above average, so 1,000 × 1.3 = 1,300 units.
Which measure expresses forecast error as a percentage of actual demand, making it useful for comparing accuracy across products with different volume scales?
Answer: MAPE
MAPE (Mean Absolute Percentage Error) normalizes error as a percentage of actual demand, enabling apples-to-apples comparison across different product volumes.
Available-to-Promise (ATP) is calculated as:
Answer: On-hand inventory plus scheduled receipts minus committed orders
ATP represents supply that is available to commit to new customer orders: on-hand inventory plus scheduled receipts, minus orders already committed.
In demand management, 'planned orders' differ from 'firm planned orders' in that firm planned orders:
Answer: Are manually frozen by planners to prevent automatic MRP changes
Firm planned orders are manually frozen by planners so that MRP does not automatically reschedule or change them during regenerative planning runs.
Which forecasting approach is most appropriate for a new product that is similar to an existing product already in the portfolio?
Answer: Analogous forecasting
Analogous forecasting uses historical demand data from a similar existing product as a proxy to estimate demand for the new product.
Which of the following actions would most directly reduce forecast error for a product with highly lumpy demand?
Answer: Collaborating with key customers to share their forward order plans
Lumpy demand is often driven by large, infrequent orders from a few customers; sharing forward order visibility eliminates the uncertainty that creates lumpiness.