RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF INFORMATIONRisk: Simple Exponential Smoothing (SES)Assignment OverviewScenario: You are a consultant for the Excellent Consulting Group (ECG). You have completed the first assignment, developing and testing a forecasting method that uses Linear Regression (LR) techniques (Module 3 Case). However, the consulting manager at ECG wants to try a different forecasting method as well. Now you decide to try Single Exponential Smoothing (SES) to forecast sales.Case AssignmentUsing this Excel template: Data Chart For BUS520 Case 4 (see attached ) do the following:Calculate the MAPE for Year 2 Linear Regression forecast (use the first spreadsheet tab labeled “Year 2 Forecast – MAPE”).Calculate forecasted sales for Year 2 using SES (use the second spreadsheet tab labeled “SES – MAPE”). Use 0.15 and 0.90 alphas.Compare the MAPE calculated for the LR forecast (#1 above) with the MAPEs calculated using SES.Then write a report to your boss in which you discuss the results obtained above. Using calculated MAPE values, make a recommendation concerning which method appears to be more accurate for the Year 2 data: SES or Linear Regression.Assignment ExpectationsAnalysisAccurate and complete SES analysis in Excel.Written ReportLength requirements: 4–5 pages minimum (not including 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 introduction to/background of the problem.Complete a written analysis that supports your Excel analysis, discussing the assumptions, rationale, and logic used to complete your SES forecast.Give complete, meaningful, and accurate recommendation(s) relating to whether LR or SES is more accurate in predicting sales.Note: Please Read attached Chapter 3,4,5 and background Reading to be clear. Also Provide Heading for Each Section of Work.