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?