# Fill in Attached spread sheet. Analytics Exercise 18-1 (Algo) Starbucks has a large, global supply chain that must efficiently supply over 17,000 stores. Although the stores might appear to be very si

Analytics Exercise 18-1 (Algo)

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        2        3       4        5        6       7       8       9      10      11      12    13

Atlanta                         43          34       33        55        35      32      45      38     32     54     28     20     56     46     36     24     55     41

Boston                          62         25       50       40        35       32      34       41     40     45     48     54     18     60      42     30     46     52

Chicago                       58         20        71       43       45       44       33     20      50      48     72      64     26     25     96     34     44     49

Dallas                           42        35        40        64     44        26        42      35     41     50      62     68     63     52     40     38     43     42

LA                                 43         41        53       45     36       33         42       48     45     46     72     40     33      44     38     48     52     48

Total                             248     155       247     247   195    167      196     182    208   243   282  246   196   227   252   174   240   232

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

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5-week MA

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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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