Reference no: EM131136826
As you complete this course, reflect back and answer these questions:
1 What two concepts do you think are the most relevant to the business and your MBA degree and why?
2 Which one or two concepts do you think are the least relevant to the business and your MBA degree and why?
Which concepts did you find particularly difficult to learn and why?
Assignment Overview
Scenario: 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 Assignment
Using this Excel template: Data chart for BUS520 Case 4, do the following:
1 Calculate the MAPE for Year 2 Linear Regression forecast (use the first spreadsheet tab labeled "Year 2 Forecast - MAPE").
2 Calculate forecasted sales for Year 2 using 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 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 Expectations
Analysis
- Accurate and complete SES analysis in Excel.
Written Report
- Length 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.
Attachment:- Case Assignment.rar
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