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2018 | Buch

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Business Case Analysis with R

Simulation Tutorials to Support Complex Business Decisions

verfasst von: Robert D. Brown III

Verlag: Apress

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and capital allocation decisions. Business case analysis, often conducted in spreadsheets, exposes decision makers to additional risks that arise just from the use of the spreadsheet environment.

R has become one of the most widely used tools for reproducible quantitative analysis, and analysts fluent in this language are in high demand. The R language, traditionally used for statistical analysis, provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis.

The main 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 supporting tutorials include the perspective of the founder of a professional service firm who wants to grow his business and a member of a strategic planning group in a biomedical device company who wants to know how much to budget in order to refine the quality of information about critical uncertainties that might affect the value of a chosen product development pathway.

What You’ll Learn

Set up a business case abstraction in an influence diagram to communicate the essence of the problem to other stakeholders

Model the inherent uncertainties in the problem with Monte Carlo simulation using the R language

Communicate the results graphically

Draw appropriate insights from the results

Develop creative decision strategies for thorough opportunity cost analysis

Calculate the value of information on critical uncertainties between competing decision strategies to set the budget for deeper data analysis

Construct appropriate information to satisfy the parameters for the Monte Carlo simulation when little or no empirical data are available

Who This Book Is For

Financial analysts, data practitioners, and risk/business professionals; also appropriate for graduate level finance, business, or data science students

Inhaltsverzeichnis

Frontmatter

Business Case Analysis with R

Frontmatter

Chapter 1. A Relief from Spreadsheet Misery

Abstract

Business case analyses that are typically developed in spreadsheets are fraught with a lack of transparency and prone to propagating significant coding errors. The R programming language provides a better alternative for creating clear and minimal-error analysis.

Robert D. Brown III

Chapter 2. Setting Up the Analysis

Abstract

The purpose of analysis is to produce and communicate effectively and clearly helpful insights about a problem. Good analysis begins with good architecture and good housekeeping of the analysis structure, elements, relationships, and style.

Robert D. Brown III

Chapter 3. Include Uncertainty in the Financial Analysis

Abstract

We incorporate potential effects of uncertainty in our analysis to account for the fact that we don’t know what will happen in the future. Monte Carlo simulation is the method that allows us to include these considerations of uncertainty analytically.

Robert D. Brown III

Chapter 4. Interpreting and Communicating Insights

Abstract

Certain graphical display devices help us to interpret and communicate powerful insights from the immense information produced by the Monte Carlo simulation process. These display devices visually communicate the range of exposure we face and the central tendency of outcomes we care about. They prioritize our attention on the risk factors that can affect us most.

Robert D. Brown III

It’s Your Move

Frontmatter

Chapter 5. “What Should I Do?”

Abstract

A few years ago, a friend of mine asked me to help him think through how to grow his business. He had successfully operated a small boutique professional services firm for several years up to that point. Now he was concerned about the demands on his personal time, his ability to save for retirement and his children’s education, and a nagging sense that things were getting a little stale. Maybe he needed a new strategy, he thought. As we discussed his current situation, he expressed the following concerns

Robert D. Brown III

Chapter 6. Use a Decision Hierarchy to Categorize Decision Types

Abstract

When it comes to making decisions associated with a given opportunity, one mistaken assumption people frequently make is to think that they need immediate resolution on every decision—right now! Very rarely is this assumption true. We need a way to identify where our attention should be focused, however, and where we can defer our attention to avoid the inefficiency of that way of thinking.

Robert D. Brown III

Chapter 7. Tame Decision Complexity by Creating a Strategy Table

Abstract

A strategy is essentially a pathway for creating value or getting more of what we want with the least expenditure from what we already possess. The amount of value we create depends on the pathway we take in the process of executing a strategy. The strategy table is a tool for developing several creative pathways that could serve us in our attempt to get to our desired goals.

Robert D. Brown III

Chapter 8. Clearly Communicate the Intentions of Decision Strategies

Abstract

The strategy table requires a good deal of thought to create, but to an outsider to the current decision process the results will look simply like a mechanical combination of alternatives. The strategy table does not communicate well the meaning and context of each decision strategy or record the thinking that went into its construction. This is the point at which we provide that context so that the decision team members can continue to discuss the strategies in a consistent manner and so that others who are not centrally involved in the planning process (yet might have some peripheral, yet important, contribution) can appreciate the direction of our thought process. We provide the context and definitions in a qualitative description or strategy rationale for each decision strategy.

Robert D. Brown III

Chapter 9. What Comes Next

Abstract

After a decision problem has been properly framed with well-designed decision strategies, it’s time to evaluate the strategies on their potential ability to create value. You must not, however, use the wrong kind of evaluation method to avoid the more difficult effort of uncertainty analysis. Do so at your own peril.

Robert D. Brown III

Subject Matter Expert Elicitation Guide

Frontmatter

Chapter 10. “What’s Your Number, Pardner?”

Abstract

Imagine that I need an important piece of information from you. It’s important because the information will be used in a business case analysis in which millions of dollars will potentially be allocated to a given project. The allocation will occur if the indicative figure of merit exceeds zero. It’s possible that the response you give me for the information I need could influence the decision to pursue the project or not, depending on the strength of the functional relationship of your information to the figure of merit. Likewise, assuming there is a strong relationship, the actual accrued value of the project could depend on the accuracy of your information in the following way, as illustrated in Figure 10-1

Robert D. Brown III

Chapter 11. Conducting SME Elicitations

Abstract

SME elicitation is the process by which we alleviate, at least temporarily, SMEs from the effects of their biases so that they can think more clearly and creatively about what the future might hold or what might veil their ability to possess certain knowledge. During the process, we facilitate an enumeration of causative factors that can affect the outcome of an uncertainty that was identified in the influence diagram, and then we assign—via the expert guidance—a measurement to the uncertain outcome as a range of probabilities that spans the range of the outcome.

Robert D. Brown III

Chapter 12. Kinds of Biases

Abstract

The field of behavioral economics has catalogued more than 100 biases and heuristics that can obstruct clear thinking or produce cognitive illusions that can lead us to misperceive the world as it really is. Rather than produce an exhaustive list here, I provide a short list of the most important ones I seem to encounter most frequently.

Robert D. Brown III

Information Espresso

Frontmatter

Chapter 13. Setting a Budget for Making Decisions Clearly

Abstract

Imagine standing beside your automobile at the starting line of a scavenger hunt and obstacle course that spans the continent from New York to Los Angeles. If you win, you will increase your income by $1 million. The trip does not come without its costs and risks, though. You will be responsible for the cost of food, fuel, and lodging. The route you take will bear a conditional effect on the travel costs as well as the cost of time. Every mile on the road will expose you to potential mechanical failures, the cost of repair and lost time, run-ins with the local gendarme, and possible roadway death. In your planning before the race (if you choose to plan at all), would you know how to choose the route that certainly results in the highest net gain?

Robert D. Brown III

Chapter 14. A More Refined Explanation of VOI

Abstract

Now that we have a notional bird’s-eye view of VOI, let’s explore how to quantitatively evaluate it from a simple instructive example. We start with a decision tree example, then move to the now familiar influence diagram representation.

Robert D. Brown III

Chapter 15. Building the Simulation in R

Abstract

As for the solution approach, you want to calculate the VOI for the problem displayed in our last influence diagram. To do so, we take the following algorithm approach.

Robert D. Brown III

Backmatter

Titel: Business Case Analysis with R
verfasst von: Robert D. Brown III
Verlag: Apress
Electronic ISBN: 978-1-4842-3495-2
Print ISBN: 978-1-4842-3494-5
DOI: https://doi.org/10.1007/978-1-4842-3495-2