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. WEEK -5 -4 -3 -2 -1 1 Atlanta 44 36 28 55 36 32 Boston 61 20 48 40 36 27 Chicago 61 24 74 43 48 45 Dallas 41 36 40 64 44 28 LA 42 40 50 45 35 32 Total 249 156 240 247 199 164 2 45 34 33 42 42 3 38 39 20 35 53 4 37 42 54 40 40 5 54 45 48 50 46 6 28 48 72 62 72 7 17 54 62 70 40 8 57 19 28 65 35 9 48 61 26 54 45 10 36 45 96 40 38 11 24 30 34 38 48 12 54 45 46 47 55 13 42 50 48 40 50 196 185 213 243 243 282 243 204 234 255 174 247 230 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 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 Week ATL BOS CHI DAL LA 1 2 3 4 5 6 7 8 9 10 11 12 13 5-week MA Week ATL BOS CHI DAL LA 1 2 3 4 5 6 7 8 9 10 11 12 13 b. Evaluate the forecasts (3-week MA and 5-week MA) 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 your answers to 2 decimal places.) MODEL ATL BOS CHI DAL LA MAD 3-week MA TS MAD 5-week MA TS 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. WEEK -5 -4 -3 -2 -1 1 Atlanta 44 36 28 55 36 32 Boston 61 20 48 40 36 27 Chicago 61 24 74 43 48 45 Dallas 41 36 40 64 44 28 LA 42 40 50 45 35 32 Total 249 156 240 247 199 164 2 45 34 33 42 42 3 38 39 20 35 53 4 37 42 54 40 40 5 54 45 48 50 46 6 28 48 72 62 72 7 17 54 62 70 40 8 57 19 28 65 35 9 48 61 26 54 45 10 36 45 96 40 38 11 24 30 34 38 48 12 54 45 46 47 55 13 42 50 48 40 50 196 185 213 243 243 282 243 204 234 255 174 247 230 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 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 Week ATL BOS CHI DAL LA 1 2 3 4 5 6 7 8 9 10 11 12 13 5-week MA Week ATL BOS CHI DAL LA 1 2 3 4 5 6 7 8 9 10 11 12 13 b. Evaluate the forecasts (3-week MA and 5-week MA) 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 your answers to 2 decimal places.) MODEL ATL BOS CHI DAL LA MAD 3-week MA TS MAD 5-week MA TS