A demand forecast is an informed estimate, not a guarantee that actual demand will match it. True or false?
2 Demand Forecasting Online Quiz Questions
Use this free practice quiz with 20 questions to review 2 Demand Forecasting, test your knowledge, and prepare for your next test or exam.
A retailer replenishes a product every week. Which forecasting setup best matches that decision?
- A
Forecast monthly demand and update it only once a year
- B
Forecast weekly demand and update it regularly
- C
Forecast demand for the next five years and do not revise it
- D
Forecast demand only after a stockout occurs
A product's demand has no clear seasonal pattern, but it has changed by an average of about 5 units per month. Which baseline method extends that average change into future periods?
- A
Mean method
- B
Naïve method
- C
Drift method
- D
Seasonal naïve method
Using the convention that forecast error equals actual demand minus forecast demand, a positive error indicates that demand was underforecast. True or false?
- A
True
- B
False
In an additive time-series pattern, seasonal effects are roughly in size as the demand level rises or falls.
A period has actual demand of zero. What is true of the percentage error for that period when calculated as part of MAPE?
- A
MAPE remains defined and equals zero
- B
MAPE is undefined
- C
MAPE is always exactly 100%
- D
MAPE becomes equal to MAE
Which practices help evaluate demand forecasts realistically? Select all correct choices.
- A
Use rolling-origin evaluation so each forecast uses only information available at that time
- B
Choose the method with the best fit to all historical observations, without holding any observations back
- C
Test forecasts at the horizons that matter for the operational decision
- D
Include later outcomes in the information used to make earlier forecasts
- E
Compare predictions with actual outcomes that were not used to produce those predictions
MAPE is undefined for a period when actual demand is .
When exploring a demand series, which business-context factors may help explain observed patterns or unusual movements? Select all correct choices.
- A
Check whether promotions or price changes may explain movements in demand
- B
Check whether holidays may create recurring or unusual demand patterns
- C
Assume a forecasting method will automatically account for every supply disruption
- D
Consider whether supply disruptions may have affected observed demand
- E
Ignore business context if the time series can be plotted
For two periods, actual demand is 10 units and 8 units, while the corresponding forecasts are 8 units and 10 units. What is the mean absolute error (MAE), in units?
A buyer has a demand forecast for a product. Explain why the forecast should not automatically become the order quantity, and describe how at least two other operational considerations could inform the replenishment decision.
A forecast has a MASE of 0.8 under a chosen benchmark scaling. What does this result indicate?
- A
The forecast is exactly 0.8 demand units too high in every period
- B
The forecast's average scaled error is better than the benchmark under the chosen scaling
- C
The forecast is guaranteed to be accurate in future periods
- D
The forecast has no errors in any period
A longer-term rise and fall in demand that does not necessarily recur at a fixed interval is a seasonal pattern.
- A
True
- B
False
A retailer replenishes a product weekly, while its manufacturer plans capacity several months ahead. Which forecasting setup best supports both decisions?
- A
Use a monthly forecast for every decision so forecasts are comparable.
- B
Use weekly forecasts for weekly replenishment and a longer horizon for capacity planning.
- C
Forecast only the next period, even when the decision concerns months ahead.
- D
Choose the horizon based on which forecast method is easiest to calculate.
A product had a stockout during several periods, and recorded sales fell during those periods. What is the most appropriate data-preparation response before forecasting?
- A
Treat all recorded sales as exact demand because sales are observed directly.
- B
Increase recorded demand in every period by the same fixed amount.
- C
Flag stockout periods because sales may understate customer demand.
- D
Delete every period with low sales, since it must reflect a stockout.
A product's usual demand rises over several years, and its busy-season increase grows in proportion to that higher level. Which description best fits this pattern?
- A
A multiplicative pattern, because seasonal swings grow in proportion to the demand level.
- B
An additive pattern, because seasonal swings grow in proportion to the demand level.
- C
A cycle, because every seasonal pattern is a long-term rise and fall without a fixed interval.
- D
Random variation, because demand is higher in some months than in others.
A planner wants to test how a forecasting process would have performed in actual use over time. Which evaluation approach best avoids using future information?
- A
Fit the model using the entire series, then compare fitted values with the same observations.
- B
At successive time points, use only data available then to forecast later observations.
- C
Randomly shuffle all observations, then use part of each period to forecast the rest.
- D
Choose the model with the smallest training error, without testing later periods.
For monthly demand with yearly seasonality, a planner forecasts next January using demand from the most recent January. Which baseline method is being used?
Actual demand was 125 units and the forecast was 140 units. Using et=yt−y^t, what is the signed forecast error in units?
A retailer’s actual demand exceeds its forecasts in many consecutive periods, rather than in just one unusual event. What forecasting issue should the retailer investigate?