Risk: Simple Exponential Smoothing (SES)

Risk: Simple Exponential Smoothin" rel="nofollow">ing (SES) Order Description Scenario: You are a consultant for the Excellent Consultin" rel="nofollow">ing Group (ECG). You have completed the first assignment, developin" rel="nofollow">ing and testin" rel="nofollow">ing a forecastin" rel="nofollow">ing method that uses Lin" rel="nofollow">inear Regression (LR) techniques (Module 3 Case). However, the consultin" rel="nofollow">ing manager at ECG wants to try a different forecastin" rel="nofollow">ing method as well. Now you decide to try Sin" rel="nofollow">ingle Exponential Smoothin" rel="nofollow">ing (SES) to forecast sales. Usin" rel="nofollow">ing the attached at Excel template: Data chart for BUS520 Case 4, do the followin" rel="nofollow">ing: 1.Calculate the MAPE for Year 2 Lin" rel="nofollow">inear Regression forecast (use the first spreadsheet tab labeled “Year 2 Forecast – MAPE”). 2.Calculate forecasted sales for Year 2 usin" rel="nofollow">ing SES (use the second spreadsheet tab labeled “SES – MAPE”). Use 0.15 and 0.90 alphas. 3.Compare the MAPE calculated for the LR forecast (#1 above) with the MAPEs calculated usin" rel="nofollow">ing SES. Then write a report to your boss in" rel="nofollow">in which you discuss the results obtain" rel="nofollow">ined above. Usin" rel="nofollow">ing calculated MAPE values, make a recommendation concernin" rel="nofollow">ing which method appears to be more accurate for the Year 2 data: SES or Lin" rel="nofollow">inear Regression. Assignment Expectations Analysis •Accurate and complete SES analysis in" rel="nofollow">in Excel. Written Report •Length requirements: 4–5 pages min" rel="nofollow">inimum (not in" rel="nofollow">includin" rel="nofollow">ing Cover and Reference pages). NOTE: You must submit 4–5 pages of written discussion and analysis. This means that you should avoid use of tables and charts as “space fillers.” •Provide a brief in" rel="nofollow">introduction to/background of the problem. •Complete a written analysis that supports your Excel analysis, discussin" rel="nofollow">ing the assumptions, rationale, and logic used to complete your SES forecast. •Give complete, meanin" rel="nofollow">ingful, and accurate recommendation(s) relatin" rel="nofollow">ing to whether LR or SES is more accurate in" rel="nofollow">in predictin" rel="nofollow">ing sales.