ECO 309 Business Forecasting Project

Overview

1. In this project, you are writing to a company Strategic Planning VP and other company executives about revenue forecast.
2. Refer to the Revenue data file under Project folder on D2L. This data file provides quarterly revenue for representative companies in the US. You are assigned one company and you can find this information in the grade on D2L. You only need the date and revenue variables.
3. Use Minitab to conduct the analysis and report your finding in the project. Make sure you:

• Write about what you are showing and why.
• Remember, Minitab results just support your findings.
• Lead the reader through your work with written narrative.
• Remember, you are selling the great work you have done with this report to the executive reader. Guide them carefully through your work. It should logically flow from objective to final revenue forecast and plans.

4. Grammars, format, and typos matter. Too many grammar mistakes and typos and inconsistent formatting will affect your grade.
5. Your wording should be narrative. It is not a combination questions and answers. The steps and questions in the guideline are for you to know what to do and discuss. However, they should be not be included in your paper, or be used to list your answers.
6. At every stage you need to answer the following questions:

• What did you do (ex: Winters’ method with these parameter values)
• Why did you do it?
• What did you find? (Interpretation of your results)
• What is your conclusion?

7. Models that will be used in the project
   • Moving Average and Smoothing Methods (Chapters 4)
   • Decomposition (Chapter 5)
   • Regression (Chapter 7&8)
   • ARIMA (Chapter 9)

Part 1—due Sunday July 12

Preparation:

First locate your assigned company revenue data in Company Revenue file under Project folder on D2L and download it to your computer. Copay and paste the data into a new Excel file, or you can copy the data to Minitab directly if comfortable with that. There should be two columns. The first column is the date and the second column is the company revenue. You do not need to use the SG&A data. Your data should start with the oldest date and end with the most recent data. Copy and paste the data to Minitab if needed. Make sure you label your data. Make sure you save the Excel file created or the Minitab spreadsheet. You will need to add more data later.

Project content:

1. Introduction –Briefly describe the business in general, such the year the company was established, the products/services the company provides, and the location of the headquarter, etc. Then discuss what you are going to do and why. For example, the objective is to develop the best two-year quarterly forecast for ____ company revenues. This is your description of the purpose and use of the forecast and plan. You may add a statement of the value of the objective to the company and its leadership.

2. Data Description–Describe your data; show time series plots and ACF from Minitab; identify the T, C and S components in the data if any.

Below is a fictional example for you to get started.  It is expected you to follow the same style: first show graphs/output from Minitab then provide text explanation for all parts of the project. Please use your own wording. Graphs/output without explanation will not be graded.

Revenue analysis for Company Fiction

(You can come up with your own title)

1. Introduction

Company Fiction was founded by First name Last name 1923. It is headquartered in City, State, Country. The company is a major electronic retailer. The purpose of this project is to…. Such analysis is important for the company…

1. Data Description

Data used in this analysis are quarterly revenue data from Company Fiction between first quarter of 1999 and last quarter of 2016. There are a total of 80 observations. Below is the summary statistics of the data.

The mean revenue is $3762.8 million with a standard deviation of $561.7 million. The highest revenue is $4919 million in the 4^th quarter of 2006 while the lowest revenue is $2278 million in the 1^st quarter of 1999.

We next examine the time series plot and ACF to determine the stationarity of the data.

Based on the plot, we can tell that the company revenue is not stationary. We can observe both an overall upward trend and seasonality.

The ACF further confirms the seasonality observed in the time series plot. The autocorrelation for the 4^th, 8^th and 12^th lags are significant.