Business Case Analysis with R
Business Case Analysis with R
A Simulation Tutorial to Support Complex Business Decisions
About the Book
Please Note: This title is no longer available here. It is now republished by Springer/Nature/Apress.
This is a tutorial for learning how to use the statistical programming language R to develop a business case simulation and analysis.
The tutorial follows the case in which a chemical manufacturing company considers constructing a chemical reactor and production facility to bring a new compound to market. There are numerous uncertainties and risks involved, including the possibility that a competitor brings a similar product online. The company must determine the value of making the decision to move forward and where they might prioritize their attention to make a more informed and robust decision. While the example used is a chemical company, the analysis structure it presents can be applied to just about any business decision, from IT projects to new product development to commercial real estate.
The purpose of the book is not to teach you R in a broad manner. Rather, it shows you how to
- Set up a business case abstraction
- Model the inherent uncertainties in the problem with Monte Carlo simulation
- Communicate the results graphically
- Draw appropriate insights from the results
About the Author
Reader Testimonials
John A Dutton
With the guidance provided by the book, I was able to develop a very useful model of climate change impacts on a hypothetical electric utility, including probabilistic demand and production of hydro and solar power.
Salil Athalye
You can spend hundreds of dollars buying college textbooks on this subject matter but many of these books don’t help you actually start implementing a system and using it. That’s why this book is a hidden gem.
Matt Marzillo
This book is a great resource for anyone looking to learn more about running simulations and getting some real world experience by test driving Robert's R code. A technical book that is easy read...for the price, it's really hard to pass up!
Carlos Ortega
The novel approach it offers is that is written in a very easy to follow R programming language. Perhaps it is the only book about this subject and entirely written in R.
Table of Contents
-
1. INTRODUCTION
- 1.1 Acknowledgments
- 1.2 Why use R for Business Case Analysis?
- 1.3 What You Will Learn
- 1.4 What You Will Need
-
2. SETTING UP THE ANALYSIS
- 2.1 The Case Study
- 2.2 Abstract the Case Study with an Influence Diagram
- 2.3 Set Up the File Structure
- 2.4 Style Guide
- 2.5 Write the Deterministic Financial Model
- 2.6 Write a Pro Forma Table
- 2.7 Conduct Deterministic Sensitivity Analysis
-
3. INCLUDE UNCERTAINTY IN THE FINANCIAL ANALYSIS
- 3.1 Why and How Do We Represent Uncertainty?
- 3.2 What is Monte Carlo Simulation?
- 3.3 The Matrix Structure of Business Case Simulation in R
- 3.4 Useful Distributions for Expert Elicited Assumptions
- 3.5 Modify the Influence Diagram to Reflect the Risk Layer
- 3.6 Include the Run Index
-
4. INTERPRETING AND COMMUNICATING INSIGHTS
- 4.1 Cash Flow and Cumulative Cash Flow with Confidence Bands
- 4.2 The Histogram of NPV
- 4.3 The Cumulative Probability Distribution of Net Present Value
- 4.4 The Waterfall Chart of the Pro Forma Present Values
- 4.5 The Tornado Sensitivity Chart
- 4.6 Closing Comments
-
5. APPENDICES
- 5.1 Appendix A - Deterministic Model
- 5.2 Appendix B - Risk Model
- 5.3 Appendix C - Finance Functions
-
6. A SPECIAL OFFER
- 6.1 How to be a Business Analytics Jedi
- 6.2 To Framing…And Beyond!
- Notes
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