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 13 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.

5-week MA Week ATL BOS CHI DAL LA Total 1 2 3 4 5 10 11 12 13b. 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. {Negative values should be indicated by a minus sign. Round all answers to 2 decimal places. Enter 'MAPE" answers as a percentage rounded to 2 decimal places.) 11 3 6 7 8 9 10 12 13 4 5 26 57 42 WEEK -5 -4 -3 - 2 -1 1 2 46 35 33 55 28 20 58 45 35 32 32 18 62 43 31 41 51 Atlanta 45 32 34 55 32 35 44 45 45 47 52 44 46 Boston 56 27 47 43 35 26 50 49 69 65 30 24 95 34 33 40 35 40 43 Chicago 50 20 64 40 40 45 35 38 48 62 68 62 47 29 28 42 45 50 50 Dallas 36 35 34 60 42 45 66 42 35 39 48 40 35 36 42 44 46 40 232 LA 41 174 184 184 212 242 272 247 203 217 255 171 232 Total 228 154 227 238 184 a. Consider using a simple moving average model. Experiment with models using five weeks' and three weeks' past data. (Round your answers to 2 decimal places.) 3-week MA Total CHI DAL LA Week ATL BOS 1 2 3 4 6 8 9 10 11 12 13