Sarbucks has a large, global supply chain that must efficiently supply over 17,000 stores. Although the stores might appear to be very Simila, 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 iIts 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. 89 10 11 12 13 Atlanta 47 32 33 57 34 35 46 35 34 54 33 21 56 45 36 25 56 40 49 23 66 42 35 41 49 WEEK -5 4-3-2 -1 2. 3. 7. Boston 60 21 43 46 33 36 33 47 40 48 47 Chicago 54 26 67 35 43 44 34 27 48 48 66 64 32 26 98 34 44 46 35 26 35 54 43 28 28 35 38 46 55 65 60 45 40 34 38 42 40 42 46 36 37 38 42 45 46 47 65 43 35 39 42 45 50 50 Dallas LA Total 236 149 224 228 190 181 183 189 206 243 266 242 206 221 250 173 229 227 a. Consider using a simple moving average model. Experiment with models using five weeks' and three weeks' past data. (Round youm answers to 2 decimal places.) 3-week MA Week ATL BOS CHI DAL LA Total 1. 3 4. 9. 10 11 12 13
Sarbucks has a large, global supply chain that must efficiently supply over 17,000 stores. Although the stores might appear to be very Simila, 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 iIts 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. 89 10 11 12 13 Atlanta 47 32 33 57 34 35 46 35 34 54 33 21 56 45 36 25 56 40 49 23 66 42 35 41 49 WEEK -5 4-3-2 -1 2. 3. 7. Boston 60 21 43 46 33 36 33 47 40 48 47 Chicago 54 26 67 35 43 44 34 27 48 48 66 64 32 26 98 34 44 46 35 26 35 54 43 28 28 35 38 46 55 65 60 45 40 34 38 42 40 42 46 36 37 38 42 45 46 47 65 43 35 39 42 45 50 50 Dallas LA Total 236 149 224 228 190 181 183 189 206 243 266 242 206 221 250 173 229 227 a. Consider using a simple moving average model. Experiment with models using five weeks' and three weeks' past data. (Round youm answers to 2 decimal places.) 3-week MA Week ATL BOS CHI DAL LA Total 1. 3 4. 9. 10 11 12 13
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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Question
How do you do this step by step?

Transcribed Image Text:Staroucks has a large, global supply chain that must efficiently supply over 17,000 stores. Although the stores might appear to be very
Similiar, 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 offerinos 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.
13
10 11
36 25 56
8
12
-5 -4 -3
Atlanta 47 32 33
WEEK
-2 -1
1
2.
3
5
57 34 35 46 35
34 54
33 21
56 45
40
60 21 43 46 33 36 33 47 40 48 47 49 23 66 42 35 41 49
66 64 32 26 90 34 44 46
45 40 34 38 42
42 45 50 50
Boston
Chicago 54 26 67
Dallas
35 43 44 34
27
48 48
28 28 35 38
46
55 65
60
35 28 35 54 43
40 42 46 36 37 38 42
LA
45
46 47
65 43 35 39
Total
236 149 224 228 190 181 183 189 206 243 266 242 206 221 250 173 229 227
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
Total
3
4
10
11
12
13

Transcribed Image Text:5-week MA
Week
ATL
BOS
Total
CHI
DAL
LA
2
3
4.
5
10
11
12
13
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.)
ATL
BOS
CHI
DAL
LA
Avg of DCs
3-week MA
MAD
MAPE
TS
5-week MA
MAD
MAPE
TS
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