Discussion Questions:

1. In the lower levels of the pyramid forecasting system, how would you prevent abdication of the

responsibility for forecasting?

2. Can a grocery store capture true demand data? How might a warehouse capture demand data?

3. Some experts have argued it's more important to have low bias (mean error) than to have a low

MAD. Why would they argue this way?

Problems:

1. Demand for stereo headphones and MP3 players for joggers has caused Nina Industries to grow

almost 50 percent over the past year. The number of joggers continues to expand, so Nina expects

demand for headsets to also expand, because, as yet no safety laws have been passed to prevent

joggers from wearing them. Demand for the stereo units for last year was as follows:

Demand Month (Units)

January

4,200

February

4,300

March

4,000

April

4,400

May

5,000

June

4,700

Demand

July

August

September

October

Month (Units)

5,300

4,900

5,400

5,700

November 6,300

December

6,000

a. Using least squares regression analysis, what would you estimate demand to be for each month

next year? Using a spreadsheet, follow the general format in Figure 3.3. Compare your results to

those obtained by using the forecast spreadsheet function.

b. To be reasonably confident of meeting demand, Nina decides to use three standard errors of

estimate for safety. How many additional units should be held to meet this level of confidence?