Jill Smith has joined recently as the forecasting manager for a consumer electronic retailer BigBuy. She is interested in developing quarterly sales forecasts for one of the company’s key products. She has collected data on quarterly sales for this product for the past 5 years and they are given in Table 2.14.

Jill decides to use Holt’s method with seasonality and trend (discussed in Example 2.6, Section 2.7) with the initial estimates of level and trend as 600 and 50, respectively. She also decides to use the first 4 years of data (2012–2015) for determining the smoothing constants (α and β) and use the 2016 data for validating the forecasting method and the smoothing constants.

a. Using the data for the first 4 years, 2012–2015, prepare the initial estimates of the seasonal factors for each quarter.

b. Using a spreadsheet, develop and select a set of good smoothing constants for both α and β for Holt’s method. Use the forecast error measures Bias and STD to test your parameters. Run your tests using the data for years 2012–2015. Use the following combinations of the smoothing constants for the tests:

c. Select the two best pairs of values for the smoothing constants (α and β) obtained from part (b) to prepare the quarterly forecasts for 2016. Using the 2016 actual sales, validate these forecasts.
Use the forecast errors Bias, STD, and tracking signals for the validation.

d. Suppose Jill wants to try out a simple moving average forecasting method, by averaging the past four quarter’s deseasonalized demands. For example, 2016 quarter 1 deseasonalized forecast will be the average of the 2015’s deseasonalized quarterly demands. Using the moving average method, prepare the quarterly forecasts for 2016. Compare these forecasts with those obtained in part (c) using the three forecast errors. Are they better than the forecasts obtained using Holt’s method? Why or why not?

e. What quarterly sales forecasts, including estimates of their accuracy, should Jill present to her company for the year 2017?

Example 2.6:
Consider the demand data for laptop computer sales for 3 years (2014–2016) given in Table 2.2. Using Holt’s method, determine the forecast for the first quarter of 2017 incorporating both seasonality and trend.

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