Starbucks has a large, global supply chain that must efficiently supply over 34,000 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	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
Los Angeles	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

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.

Note: Round your answers to 2 decimal places.

ES, = 0.2. compute weeks 1-13 for atlanta, boston chicago dallas los angeles and total