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	44	35	28	55	35	32	45	35	32	54	28	18	58	48	36	24	56	42
Boston	61	24	48	40	35	27	35	42	42	45	48	53	20	61	45	30	46	50
Chicago	61	23	74	43	45	45	33	23	53	48	72	60	27	26	96	34	45	48
Dallas	41	35	40	64	44	28	42	34	40	50	62	68	64	54	40	38	45	40
LA	42	42	50	45	36	32	42	50	42	46	72	42	34	45	38	48	55	50
Total	249	159	240	247	195	164	197	184	209	243	282	241	203	234	255	174	247	230

a. Consider using a simple exponential smoothing model. In your analysis, test two alpha values, 0.2 and 0.4. When using an alpha value of 0.2, assume that the forecast for week 1 is the past three-week average (the average demand for periods 3, 2, and 1). For the model using an alpha of 0.4, assume that the forecast for week 1 is the past five-week average. (Round your answers to 2 decimal places.)

ES, = 0.2

Week	ATL	BOS	CHI	DAL	LA	TOTAL
1
2
3
4
5
6
7
8
9
10
11
12
13

ES, = 0.4

ES, = 0.2

Week	ATL	BOS	CHI	DAL	LA	TOTAL
1
2
3
4
5
6
7
8
9
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 DC's
ES, a = .2	MAD
	MAPE
	TS
ES, a = .4	MAD
	MAPE
	TS