Chapter 3
Part I: Answer the following questions:
1. What is a qualitative forecasting model, and when is its use appropriate?
2. Identify and briefly describe the two general forecasting approaches.
3. Suppose you need to forecast the amount of relief aid needed following an earthquake.
Which type of forecast do you think is the most appropriate: qualitative or quantitative?
Why? Is collaborative planning, forecasting, and replenishment (CPFR) applicable in this
case?
4. Briefly describe the steps that are used to develop a forecasting system.
5. A skeptical manager asks what medium-range forecasts can be used for. Give the manager
three possible uses/purposes.
6. Explain why such forecasting devices as moving averages, weighted moving averages, and
exponential smoothing are not well suited for data series that have trends.
7. What is the basic difference between a weighted moving average and exponential
smoothing?
8. What three methods are used to determine the accuracy of any given forecasting method?
How would you determine whether time-series regression or exponential smoothing is
better in a specific application?
9. Research and briefly describe the Delphi technique. How would it be used by an employer
you have worked for?
10. What is the primary difference between a time-series model and an associative model?
11. What type of forecasting method would you recommend to a start-up retailer in terms of
quantity, number of products, etc.? Would you use the same method after, say, 5 years of
operation? Explain.
12. What effect does the value of the smoothing constant have on the weight given to the recent
values?
13. Explain the value of seasonal indices in forecasting. How are seasonal patterns different
from cyclical patterns?
14. Which forecasting technique can place the most emphasis on recent values? How does it
do this?
15. How can an exponential smoothing model be made more responsive?
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