Consider the "Analytics Exercise: Forecasting Supply Chain Demand-Starbucks Corporation" at the end
Question 1 (40 marks) Consider the "Analytics Exercise: Forecasting...
Question 1 (40 marks)
Consider the "Analytics Exercise: Forecasting Supply Chain Demand-Starbucks Corporation" at the end of Chapter 18 in your course textbook. Open a blank Excel workbook, and rename the second tab as Q1starbuck-partA. The remaining tabs should be renamed as Q1starbuck-partB, Q1starbuck-partC, Q1starbuck-partD, Q1starbuck-partE, and Q1starbuck-partF. The following questions should be analyzed in Excel and answered using textboxes in the same tab.
Part A (8 marks)
You will develop simple moving average forecast based on the past 5 weeks and the past 3 weeks of data and find the MAD, MSE, MAPE, and tracking signal of your forecast. Which forecast, the 5-week or the 3-week, is more accurate for each of the distribution centres? Provide a rationale for its better accuracy for that particular warehouse using a text box.
Part B (8 marks)
Following the question on the next page of the exercise in your textbook, you will develop exponential smoothing forecast based on alpha = 0.2 and alpha = 0.4 and find the MAD, MSE, MAPE, and tracking signal of your forecast. Which forecast, alpha=0.2 or alpha =0.4, is more accurate for each of the distribution centres? Which value of alpha emphasizes more on the past data?
Part C (8 marks)
Starbucks is planning to consolidate the five distribution centres into one with the aggregated demand represented by the total row. Perform forecasts for the 3-week moving average, 5-week moving average, 0.2 alpha exponential smoothing, and 0.4 alpha exponential smoothing on the aggregated total demand. After comparing the results and accuracy measures, provide a rationale on which of these four forecasting methods you would recommend to Starbucks.
Part D (8 marks)
Starbucks also wants you to develop a linear regression model based on the total demand data for Week -1 to -5. Use this model to predict the total aggregated demand for Week 1 to Week 13, and find the forecast accuracy in terms of MAD, MSE, and MAPE. Does linear regression outperform your suggested method in Part C of this question in terms of accuracy measures?
Part E (4 marks)
Discuss any two pros and two cons of aggregating demand of these five distribution centres.
Part F (4 marks)
Part A: The 3-week moving average forecast is more accurate for each of the distribution centres because it
One benefit of making a new prediction based on old ones is that it takes into account any mistakes that might have been made in the past. By looking at past predictions, it is possible to make more accurate predictions in the future by taking into account any mistakes that were made in the past and fixing them. This can help make sure that plans for the future are more accurate.
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