Business Case Analysis with R: A Simulation Tutorial to Support Complex Business Decisions
Book Details
Author(s)
Robert Brown
ISBN / ASIN
B00DXMN0E0
ISBN-13
978B00DXMN0E2
Sales Rank
#590,270
Marketplace
United States 🇺🇸
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Description
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 undertainties 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.
The purpose of the book is not to teach you R in a broad manner. Rather, it will attempt to show you how to
* Set up the business case abstraction
* Model the inherent uncertainties in the problem with Monte Carlo simulation
* Communicate the results graphically
* Draw appropriate insights from the results
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 Including 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
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 undertainties 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.
The purpose of the book is not to teach you R in a broad manner. Rather, it will attempt to show you how to
* Set up the business case abstraction
* Model the inherent uncertainties in the problem with Monte Carlo simulation
* Communicate the results graphically
* Draw appropriate insights from the results
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 Including 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
