# Exponential Smoothing Forecasting and Value of Information

Case Background

What if you cannot find another factor that has a high correlation with the forecasted factor? Are there other forecasting methods other than Linear Regression? How do you determine which method is actually the best one?

Chase, C. W., (2013). Demand-driven forecasting: A structured approach to forecasting. John Wiley & Sons. Somerset, NJ. Retrieved from Ebrary.

•Chapter 3, pp. 91–93 (the section Some Causes of Forecast Error)
•Chapter 4, pp. 103–113, which provides information on forecast error measures; pay special attention to the sections on the MAPE measurement
•Chapter 5, pp. 125–147; pay attention the sections on Simple Exponential Smoothing (SES)

Download the Excel file Case 4 Examples-Practice.xlsx that contains an example and a Practice Exercise.

PRACTICE: Do the Practice Exercise in the Excel file: Case 4 Examples – Practice-Excel. Check your work.

You are ready to do the Case 4 problem.

SLP Background

Consider that you may be pretty good sometimes at estimating future probabilities. But you also acknowledge that you might be biased, too. This is where experts are useful, although they do charge a fee for their services. What is the value of the information you could get from an expert? Is it worth paying this expert for his/her advice? Read the paper SLP 4-Deciding to Use an Expert.docx that explains how to make this decision.

Download the Excel file SLP 4 Examples-Practice.xlsx that provides examples and a Practice Exercise.

Watch this video showing how to determine the value of information: https://permalink.fliqz.com/aspx/permalink.aspx?at=f616909cae2d4d06834359502f672aff&a=5fae3cf0f1624f39b0341263a6541ea0

Practice determining the Value of Information; do the Practice Exercise in the Excel file.

You are ready for SLP 4.

(For Discussions, Module 2, 3, and 4)

Download and read Subjective Assessments of Risk and Uncertainty on subjective probabilities in risk decisions. This paper will be useful for the discussion questions in Module 2, 3, and 4.

Get this journal article from the library. It is lengthy, but you only need to read Section 1.1, pp. 3-5. This section provides a very good review of three major biases that have been studied by the famous team of Kahneman and Tversky.

Laibson, D., & Zeckhauser, R. (1998). Amos Tversky and the ascent of behavioral economics. Journal of Risk & Uncertainty. Feb1998, Vol. 16 Issue 1, p7-47. 41p. Retrieved from Business Source Complete (EBSCO) in the Trident Online Library.

Module 4 – Case ( Writer: Please only write 4 pages for this case)

Risk: Exponential Smoothing Forecasting and Value of Information

Assignment Overview

Scenario: You are still a consultant for the Excellent Consulting Group. You have completed the first assignment, developing and testing a forecasting method based on linear regression (Case 3). However, your consulting manager at ECG wants to go the next step and investigate another forecasting method. It is important to do a thorough job for the client, and you have the expertise to analyze different forecasting methods. You have decided to look at the sales data for client’s lottery app as a single data set and use a time series analysis, namely SES, single exponential smoothing.

Case Assignment

Using Excel, use the forecasted sales from Case 3 to compute the MAPE, by doing the following:
1.Calculate the MAPE for the first 12 months (assume the forecast for Month 1 – or January – is equal to January’s actual sales). Use 0.15 and 0.90 alphas.
2.Using the forecasted sales for Feb – April (taken from the Case 3 Linear Regression exercise), compute the MAPE by comparing actual sales for each month, or Y(t) to forecasted sales, or F(t). Compare this 3-month MAPE to the two MAPE values you calculated in your SES analysis above. Use the following table:

Month

Sales, Y(t)

Sales F(t)

Y(t) – F(t)

PE

APE

February

?

?

?

?

?

March

?

?

?

?

?

April

?

?

?

?

?

?

?

?

ME

MPE

MAPE

Then write a report to your boss that briefly describes the results that you obtained. Using MAPE values, make a recommendation on which method appears to be more accurate — SES or Linear Regression.

Data: Use the data that you previously have generated from your analyses in Case 3.

Assignment Expectations

Analysis
•Accurate and complete SES analysis in Excel.

Written Report
•Length requirements = 4–5 pages minimum (not including Cover and Reference pages)
•Provide a brief introduction/ background of the problem.
•Complete and accurate Excel analysis.
•Written analysis that supports Excel analysis, and provides thorough discussion of assumptions, rationale, and logic used.
•Complete, meaningful, and accurate recommendation(s).

Module 4 – SLP ( Writer: please write only 2 pages for this case)

Risk: Exponential Smoothing Forecasting and Value of Information

Scenario: Using the same situation from SLP 3, recall that you are deciding between three investments. You have heard of an Expert who has a “track record” of high confidence in correctly identifying when market conditions are favorable or not. You are now considering whether to consult this “expert” and if it would be worth paying his fee to get his prediction. So you are going to do further analysis to determine the value of this information that the expert might provide.

In order to simply the analysis a bit, you have decided to look at two possible outcomes for each alternative instead of three. You are interested in whether the market will be Favorable or Unfavorable, so you have collapsed the Medium and Low outcomes. Here are the three alternatives with the adjusted NPV outcome and probabilities.

Option A: Real estate development. This is a risky opportunity with the possibility of a high payoff, but also with no payoff at all. You have reviewed all of the possible data for the outcomes in the next 10 years and these are your estimates of the Net Present Value of the cash flow and probabilities.
High/Favorable NPV: \$5 million, Pr = 0.5
Unfavorable NPV: \$1.2 million, Pr = 0.5

Option B: Retail franchise for Just Hats, a boutique type store selling fashion hats for men and women. This also is a risky opportunity but less so than option A. It has the potential for less risk of failure, but also a lower payoff. You have reviewed all of the possible data for the outcomes in the next 10 years and these are your estimates of the Net Present Value of the cash flow and probabilities.

High/Favorable NPV: \$3.4 million, Pr = 0.75

Unfavorable NPV: \$2 million, Pr = 0.25

Note that this option requires less investment, so there is \$0.2 million available, which will be invested in the same bonds as Option C. The NPV of this investment in this option (B) is \$0.4 million. This has been added to NPV for the Favorable and Unfavorable outcomes of the boutique.

Option C: High Yield Municipal Bonds. This option has low risk and is assumed to be a Certainty. So there is only one outcome with probability of 1.0

NPV: \$1.5 million, Pr = 1.0

You have contacted the Expert and received a letter stating his track record which you have checked out by several resources. Here is his stated track record:

True State of the Market

Expert Prediction

Favorable

Unfavorable

Predicts “Favorable”

.9

.3

Predicts “Unfavorable”

.1

.7

You realize that this situation is a bit complicated since it requires the expert to analyze and predict the state of two different markets: the real estate market and the retail hat market. You think through the issues of probabilities and how to calculate the joint probabilities of both markets going up, both going down, or one up and the other down. Base on your original estimates of success, here are your calculations of the single probabilities and joint probabilities of the markets.

Probabilities

Favorable

Unfavorable

A: Real Estate

0.50

0.50

B: Just Hats

0.75

0.25

Joint Probabilities

A Fav, B Fav (A+, B+)

0.375

A Unf, B Unf (A-, B-)

0.125

A Fav, B Unf (A+, B-)

0.125

A Unf, B Fav (A-, B+)

0.375

Finally, after a great deal of analysis and calculations, you have determined the Posterior probabilities of Favorable and Unfavorable Markets for the Real Estate business and the boutique hat business.

Real Estate

Just Hats

F

U

F

U

0.45

says “F/F”

0.75

0.25

0.90

0.10

0.15

says “F/U”

0.75

0.25

0.30

0.70

0.30

says “U/F”

0.125

0.875

0.90

0.10

0.10

says “U/U”

0.125

0.875

0.30

0.70

For example, this table says that there is 45% chance that the expert will predict Favorable for both markets (F/F), and when he makes this prediction, there is a 75% chance that the Real Estate market will be favorable and 25% chance that it won’t, and also a 90% chance that the Hat market will be Favorable and 10% chance it won’t.

You have developed a decision tree showing the original collapsed solution and also showing an expanded decision tree for evaluating the value of the expert’s information. You need to enter the probabilities into this tree to see if the expert’s information will increase the overall expected value of your decision. Download the Excel file with the incomplete decision tree. SLP 4-Decision Tree.xlsx

Assignment

Complete the information in the decision tree in the Excel file. Determine the Expected NPV of the decision if you were to consult the Expert. Does this increase the value of your analysis? By how much?

Upload both your written report and Excel file with the Decision Tree analysis to the SLP4 Dropbox.

SLP Assignment Expectations

Analysis
•Accurate and complete analysis in Excel.

Required:
•Length requirements = 2–3 pages minimum (not including Cover and Reference pages)
•Provide a brief introduction/ background of the problem.
•Complete and accurate Excel analysis.
•Written analysis that supports Excel analysis, and provides thorough discussion of assumptions, rationale, and logic used.
•Complete, meaningful, and accurate recommendation(s).
And Finally, We Reflect Back on the Course…
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Writer: Please write only 1 page for this reflection paper:

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?
3. Which concepts did you find particularly difficult to learn and why?