Module 7: Project

This group project is designed to provide you with hands-on strategic analysis experience. If the CEO of your company assigned you a project to analyze a strategic situation, what would you deliver? You have learned a number of forecasting techniques throughout this course. Review Table 10.2: A Guide to Selecting an Appropriate Forecasting Method in your textbook, which contains guidelines for model selection. It might be useful to consider the nine steps in forecast implementation as well as the forecasting techniques for your group project. Refer to this video to understand the requirements and my expectations for your group project:

Video: A Guide to Your Final Project

Select Play to learn more. You can also refer to the given video transcript Download video transcript.

SAMPLE PROJECTS

When using one of the exponential methods, you will need to choose smoothing parameters such as alpha, beta, and gamma. Start by assigning a random number to each parameter between 0 and 1, then forecast your sales and calculate your RMSE or any other measure you choose to evaluate the performance. Next, use Excel Solver to find the optimal alpha, beta, and gamma values that minimize RMSE.

To learn how to do this, please watch the following videos on Netflix’s Holt’s Method or Amazon’s Winter’s Method below.

Netflix Revenue Holts MethodLinks to an external site.

Amazon Revenue Winter’s MethodLinks to an external site.

Netflix sales provide a great example of a dataset with a trend but no seasonal variations. I used Holt’s Exponential Smoothing and Quadratic Trend model to forecast the sales. Amazon sales both trend and vary seasonally. I used Winter’s Exponential Smoothing and Multiple Regression with dummies to forecast the sales.

Netflix Revenue Quadratic Trend ModelLinks to an external site.

Amazon Revenue Multiple Linear Regression with DummiesLinks to an external site.

You can find the Excel files below:

Netflix RevenueDownload Netflix Revenue

Amazon RevenueDownload Amazon Revenue

Instructions

In Week 2, your instructor divided the class into pairs. By the end of Week 3, your group selected the company to investigate. By the end of Week 4, the company selection was finalized. In Weeks 5 and 6, you should have analyzed the data and performed the required forecasts.

This week, your group will forecast monthly or quarterly sales (in units or dollars) for your chosen company. As a group, you will write a paper about your findings.

Paper Requirements

Prepare a two-year (8 quarter or 24 month) forecast of the series. As a group, you must use two separate methods. One student will use an appropriate extrapolation method, which is usually an exponential smoothing method. The other student will use a causal regression model. You will present your results in a paper that should be analytically accurate and should clearly communicate your process to your manager.

The paper should be 8–10 pages in length, including tables and figures, and must include only these sections:

Title Page: Include company name, your name, and an appropriate “Table of Contents” (listing page numbers for the following sections).

Section 1 – Introduction: Why did you select this topic? How would this forecast be useful? To whom would it be useful? (1 page)

Section 2 – Literature Review: Present information about the company and industry. This section is not about forecasting methods (1 or 2 pages).

Section 3 – Managerial Overview of Methods Used: Why did you select these forecasting methods? Explain why you believe the technique you have chosen is appropriate to forecast your data (1 or 2 pages).

Section 4 – Application of Forecasting Methods and Results: What are the forecast results of these methods? Which method performs better? How did you evaluate the forecasting methods? Present your forecast results and explain the methods you used to evaluate your forecast results (2 to 4 pages).

Section 5 – Conclusions and Limitations: (1 page)

Section 6 – References: Cite 6 to 8 references related to the company selected (1 page).

Appendix: Include one or more appendices containing appropriate graphics and a complete professional listing of data with appropriate citations. All graphs in the appendix must be referenced in the body of your paper along with the page on which each graph can be found.

The paper should be typed, single-spaced, and presented in 12-point Times New Roman font.

Excel File Requirements

When you submit your paper, you must also submit an Excel file including your data and analysis.

Tab 1 – Basic Data: Show the dates in column A and the sales data in column B.

Tab 2 – Extrapolation Model: Show the data you used for your extrapolation method with the dates in column A, the sales data in column B, and the predicted values for that method in column C.

Tab 3 – Regression Model: Show all the data used in the regression model with dates in column A and the sales data in column B. The next columns in Tab 3 should include all the independent variables used in your regression model. Following these columns, you should add a column containing the values predicted by the regression analysis.

Tab 4 – Final Forecasts: The fourth and final tab should have the dates in column A, the original sales data in column B, the predicted values from your extrapolation forecast in column C, and the predicted values from your regression model in column D. The predicted values will extend 8 quarters (or 24 months) beyond the actual historic values.

Discussion

You are required to read, reflect on, and respond to at least one project paper. You will post your contribution to the topic “Projects” on the Discussion Board. Your contribution to the discussion about papers should be clear, complete, and accurate. In your reflection on the paper, you should cover at least two of the following:

• Offer an additional method or variable(s) to include in a forecasting technique to predict sales. Please explain your reasons for the new method or variable you propose.
• Suggest ways in which a forecasting technique could be more clearly expressed.
• Identify passages where you think the writer misinterpreted, or incorrectly applied, a concept.
• Offer your assessment of the forecast results, and explain why you agree or disagree with the prediction.

Recommended Information Sources

Research Insight (RI): This database from Standard & Poor’s offers up to 20 years and up to 48 quarters of historical financial information on public U.S. and Canadian companies.

SEC’s EDGAR Database: The Securities Exchange Commission (SEC) maintains a database of SEC filings by public companies. The 10-K reports contain much of the same information found in annual reports and will be the most useful for this assignment.

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