Read the Forecasting Supply Chain Demand – Starbucks Corporation case in your text Operations and Supply Chain Management on pages 484-485, then address the four questions associated with the Starbucks case on page 485. 

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ANALYTICS EXERCISE: FORECASTING SUPPLY CHAIN DEMAND-STARBUCKS CORPORATION (LO3–2) As we discussed at the beginning of the chapter, 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. The demand at the distribution centers (DCs) varies between about 40 units on average per week in Atlanta and 48 units in Dallas. The current quarter's data are pretty close to the demand shown in the table. 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. Page 90 WEEK 1 2 3 4 5 6 7 8 9 10 11 12 13 AVERAGE Atlanta 33 45 37 38 55 30 18 58 47 37 23 55 40 40 Boston 26 35 41 40 46 48 55 18 62 44 30 45 50 42 Chicago 44 34 22 55 48 72 62 28 27 95 35 45 47 47 Dallas 27 42 35 40 51 64 70 65 55 43 38 47 42 48 LA 32 43 54 40 46 74 40 35 45 38 48 56 50 46 Total 162 199 189 213 246 288 245 204 236 257 174 248 229 222 ANALYTICS EXERCISE: FORECASTING SUPPLY CHAIN DEMAND-STARBUCKS CORPORATION (LO3–2) As we discussed at the beginning of the chapter, 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. The demand at the distribution centers (DCs) varies between about 40 units on average per week in Atlanta and 48 units in Dallas. The current quarter's data are pretty close to the demand shown in the table. 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. Page 90 WEEK 1 2 3 4 5 6 7 8 9 10 11 12 13 AVERAGE Atlanta 33 45 37 38 55 30 18 58 47 37 23 55 40 40 Boston 26 35 41 40 46 48 55 18 62 44 30 45 50 42 Chicago 44 34 22 55 48 72 62 28 27 95 35 45 47 47 Dallas 27 42 35 40 51 64 70 65 55 43 38 47 42 48 LA 32 43 54 40 46 74 40 35 45 38 48 56 50 46 Total 162 199 189 213 246 288 245 204 236 257 174 248 229 222

Answer rating: 100% (QA)

Solution Forecast the 5 weeks moving average and 3 weeks ... View the full answer