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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

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 lets 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 2 3 4 5 6 7 8 9 10 11 12 13 Atlanta 45 35 30 55 35 30 45 35 30 54 28 20 58 46 36 24 56 41 Boston 60 24 50 40 35 30 34 40 41 45 48 54 20 60 45 30 46 52 Chicago 62 23 71 43 45 45 33 23 53 48 72 64 27 25 96 34 45 47 Dallas 40 35 40 64 44 28 42 34 40 50 62 68 64 52 40 38 45 42 LA 44 42 52 45 36 34 42 50 44 46 72 40 34 44 38 48 55 48 Total 251 159 243 247 195 167 196 182 208 243 282 246 203 227 255 174 247 230 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 5-week MA 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. (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.)

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image text in transcribed Starbucks has a large, global supply chain that must efficlently 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 avallable 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 retall stores. The coffeemaker has been a steady seller over the years due to its rellability and rugged construction. Starbucks does not consider this a seasonal product, but there is some varlability 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 exponentlal smoothing. 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.) 5-week MA 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 criterla. (Negatlve values should be Indlcated by a minus sign. Round all answers to 2 decimal places. Enter "MAPE" answers as a percentage rounded to 2 decimal places.)

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