Hello can you please show the example using excel?

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 18 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 48 42 36 54 34 32 49 40 44 50 31 20 60 51 38 26 53 42 Boston 65 22 54 36 32 25 39 44 46 41 49 57 20 66 45 33 43 52 Chicago 65 26 78 40 45 43 38 25 61 43 73 64 30 31 96 38 43 49 Dallas 45 39 46 60 40 26 46 38 46 46 65 72 67 59 44 41 45 44 LA 46 44 60 42 32 31 47 57 46 41 75 42 37 49 39 51 54 52 Total 269 173 274 232 183 157 219 204 243 221 293 255 214 256 262 189 238 239

1. 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.) 2. 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.) 3. Consider using an adjusted exponential smoothing model. In your analysis, use betta value 0.3 with 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.) 4. 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 deviation, and mean squared error as criteria. (Round your answers to 2 decimal places. Negative amount should be indicated by a minus sign.) 5. Based on the forecast accuracy estimates which forecasting method performs better? Justify your conclusion.