Starbucks has a large, global supply chain that must efficiently supply over 17,000 stores. Although the stores might appear to be very similar, they are actually very different. Depending on the location of the store, its size, and the profile of the customers served, Starbucks management configures the store offerings to take maximum advantage of the space available and customer preferences. Starbucks’ actual distribution system is much more complex, but for the purpose of our exercise let’s focus on a single item that is currently distributed through five distribution centers in the United States. Our item is a logo branded coffeemaker that is sold at some of the larger retail stores. The coffeemaker has been a steady seller over the years due to its reliability and rugged construction. Starbucks does not consider this a seasonal product, but there is some variability in demand. Demand for the product over the past 18 weeks is shown in the following table. (week −1 is the week before week 1 in the table, −2 is two weeks before week 1, etc.).

Management would like you to experiment with some forecasting models to determine what should be used in a new system to be implemented. The new system is programmed to use one of two forecasting models: simple moving average or exponential smoothing.

WEEK −5 −4 −3 −2 −1 1 2 3 4 5 6 7 8 9 10 11 12 13
Atlanta 35 34 33 58 32 32 46 35 33 54 30 20 58 46 35 26 57 42
Boston 58 29 49 45 33 34 33 45 42 46 49 55 21 64 45 33 43 53
Chicago 53 24 62 40 40 45 33 26 50 47 65 65 30 25 95 34 44 48
Dallas 36 30 34 55 40 28 28 35 38 47 60 68 62 45 40 35 46 43
LA 42 42 46 38 36 36 42 44 46 46 66 42 35 39 42 45 50 50
Total 224 159 224 236 181 175 182 185 209 240 270 250 206 219 257 173 240 236

Required:
a. Consider using a simple moving average model. Experiment with models using five weeks’ and three weeks’ past data.
b. Evaluate the forecasts that would have been made over the 13 weeks using the overall (at the end of the 13 weeks) mean absolute deviation, mean absolute percent error, and tracking signal as criteria.