Example 16.8

Forecasting Quarterly Soft Drink Sales

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Soft Drink Sales.xlsx

• The data in this file represent quarterly sales (in millions of dollars) for a large soft drink company from quarter 1 of 1990 through quarter 1 of 2005.

• As we might expect, there has been an upward trend in sales during this period, and there is also a fairly regular seasonal pattern, as shown on the next slide.

• Sales in the warmer quarters, 2 and 3, are consistently higher than in the colder quarters, 1 and 4. How well can Winters’ method track this upward trend and seasonal pattern?

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Solultion

• The procedure required for Winters’method is practically the same as for Holt’s method.

• We again create a data set with StatTools, and then we fill in the dialog box for forecast settings as shown on the next slide.

• The only difference is that when we check theWinters’ option, an extra smoothing constant (for seasonality) appears.

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Discussion of the Results

• The StatTools output for Winters’ method is very similar to the Holt’s method output.

• The summary section on the next slide shows the optimal smoothing constants, which produce a MAPE of 4.41%.

• Again, you can manually try other smoothing constants in the range B9:B11 to see how sensitive the summary measures are to the smoothing constants.

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Discussion of the Results -- continued

• The detailed data section shown on the next slide implements the exponential smoothing equations for Winters’ method.

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright

Discussion of the Results -- continued

• The chart on the next slide indicates how well Winters’ method (with these smoothing constants) tracks the sales pattern through time.

• It even picks up the slight decrease in the upward trend in more recent years and projects this pattern into the future.

• If we had used Holt’s method on this data set, it would have identified the upward trend, but it would have completely missed the seasonal pattern.

Thomson/South-Western 2007 ©South-Western/Cengage Learning © 2009Practical Management Science, Revised 3eWinston/Albright