CHAPTER 1

Project Decision Analysis

What Is It?

Most of us believe we are pretty good at making decisions, yet we continue to make poor ones. And over time our poor decisions become a burden that we impose on each other, especially when the decisions we make as managers are connected to large-scale projects that affect many people. The process known as structured decision analysis—which is described in detail in this book—can improve our ability to make better decisions, particularly in project management, where the decisions can be complex. Indeed, today many organizations in both the public and private sectors use decision analysis to solve their project management problems.

The Burden of Poor Decision-Making

In the summer of 2017, several South Carolina utility companies decided to halt the construction of two new nuclear reactors on the V.C. Summer nuclear project (Plumer 2017). The project was originally planned to be completed in 2018 and cost $11.5 billion. In 2017 it was determined that the reactors would not begin generating electricity before 2021 and could cost as much as $25 billion. The companies had spent over $9 billion before canceling the project, and the reactors were only 40% completed. The reactors were meant to be the vanguard of a nuclear comeback as the United States had built no nuclear reactors since the 1970s. Instead, the halting of this project was a major setback for U.S. ambitions to reinvigorate the nuclear power industry. Currently, the Alvin W. Vogtle Electric Generating Plant, in Georgia, remains the only nuclear power plant under construction in the country, and it too faces enormous cost overruns and delays.

So, “What went wrong?” This question should always be asked in such cases. First, utility companies selected an advanced reactor design from Westinghouse Electric Company, the AP1000. However, when construction started, new features were incorporated into the design that caused significant re-engineering. In addition, since no new reactors had been built for some 40 years, supply chain and engineering expertise had been lost. In the resulting mess, Westinghouse, the company responsible for the plant’s design and construction, filed for bankruptcy and the utilities companies decided to accept the losses rather than pass on the costs to consumers.

We all remember that our parents always told us to “think before you do something.” Apparently, the people who sanctioned, planned, and executed this nuclear project failed to think about all the possible implications before making their decisions. Perhaps this was an isolated incident, or perhaps it was an emerging trend, never before seen? Here is another example:

In 2004–2005, Governor Arnold Schwarzenegger of California was involved in a complex decision-making process. He was not considering a role for his next action movie after he left office, nor was he selecting a new energy weapon to blast villains in a sci-fi movie. This was something more serious: the governor involved himself in the design process for a new bridge in San Francisco (Cabanatuan 2005).

This was not just any bridge. The $6.3 billion project (figure 1-1) was to replace the existing Bay Bridge. The original plans called for the section of the bridge east of Yerba Buena Island to include a huge suspension span. Although the construction of the foundations for the suspension span had started a few years earlier, the governor’s office insisted that a simple viaduct would be cheaper and faster to build. Transportation officials did not agree, believing that a design change from a suspension span to a viaduct would slow construction.

Early in 2005 the governor’s side appeared to have prevailed: work on the foundation was halted, and the contract was terminated. A few months later, however, following a detailed analysis, both sides agreed to follow the original design, which included the suspension span. In the end, the fight over the bridge design cost $81 million.

Figure 1-1. San Francisco Bay Bridge Construction (Photo by Oleg Alexandrov)

If you do not live in Northern California, you may not be directly affected by the Bay Bridge cost overrun. However, directly or indirectly, at some time you will pay for somebody’s wrong decision—regardless of where you live or what you do. This is because, for example:

• Costs related to problems in developing new drugs are passed on to consumers in the form of higher prices for medications.

• Dry wells lead to increased costs for oil and gas exploration and production, leading in turn to higher prices at the gas pump.

• Governments sometimes implement ill-considered policies that can adversely affect your taxes.

• You yourself occasionally make wrong decisions. The cheap brand of deck coating that you used to save a couple of dollars is already peeling off and you will have to paint your deck again next year (next time with a better brand).

Problems result from poor decision-making, whether the person making the decision is the manager at the pharmaceutical company, the geologist making a bad choice of where to drill for oil, the ineffective government bureaucrat or legislator making policy for the wrong reasons, or even you yourself, trying to save a few bucks by buying a low-priced deck coat.

We human beings have been making poor decisions since we first developed the ability—and the necessity—to make choices. In the modern world, however, due to the complexity and cost of projects, the price we pay for poor decisions has significantly increased. The overall cost of wrong decisions is very hard to estimate, but it is undoubtedly enormous. Say, for example, we design a multibillion-dollar oil pipeline but make a poor decision on the path it will follow through a particular location. Because of that poor decision, we now have to move it—a step that might increase the project costs by millions of dollars. Who pays that cost? It is passed on to somebody—investors, consumers, or the government.

Poor decision-making in the medical field can have expensive, even fatal, results. The causes of medical mistakes differ. Sometimes the cause is a flaw in a hospital procedure. Most medical mistakes, however, are related to errors in human judgment. In the United States, more than 250,000 deaths per year are the result of medical errors (Makary and Daniel 2016). As a comparison, according to the Centers for Disease Control, in 2013 a total of 611,105 people died of heart disease, 584,881 of cancer, and 149,205 of chronic respiratory disease—the top three causes of death in the nation.

Why Do We Make Wrong Decisions?

Lawrence Phillips, a prominent decision analysis expert, cites a curious paradox: although the ability to make right decisions is considered a main indicator of project-management professionalism, many project managers are unwilling to try to improve the quality of their decisions (Goodwin 2014). Phillips suggests that many people consider decision-making to be merely an automatic process, as natural as breathing. And if we don’t need to learn how to breathe, why do we need to learn how to make better decisions? With such a blasé attitude, many project managers don’t make the effort to understand decision analysis, or perhaps they believe that it is just a theoretical discipline with no practical use in their work.

If you were asked to rate your decision-making ability, most likely you would rate yourself as “better than average.” The “better-than-average effect,” where people tend to rate themselves as above average when asked to characterize their abilities, is a common psychological bias (Massey, Robinson and Kaniel 2006) that is applicable not only to self-assessments of decision-making but also to other activities. But, if we believe that we are such good decision-makers, why do we often make poor ones?

The answer resides in the fact that most of today’s important project-management decisions are complex. Without proper analysis, it is hard to make choices between alternatives. Every day, project managers make numerous decisions. Most of them are trivial and do not require sophisticated analysis. If a component for your construction project is delayed, you might decide to call the supplier. Obviously, in making this choice, you can rely on common sense. You do not need to perform an advanced analysis, solve a few differential equations, or run a complex simulation model. However, if you need to select a new supplier, the situation is quite different. A great deal is at stake, and a wrong decision could be very costly. In addition, you likely have many alternatives. So, now you realize that relying solely on your intuition may not be enough; you probably should perform a decision analysis.

Why is decision-making so complicated? It’s true for a number of reasons:

• Most problems in project management involve multiple objectives. Tesla’s Model 3 was planned to be an affordable, reliable, sporty, fuel-efficient, high-tech, luxurious, and practical mass-produced electric car (Grinshpun 2018). Production of such an ambitious product faced many challenges: the supply chain management needed to be built from scratch, new manufacturing processes needed to be developed, and distribution and delivery processes required implementation. Finally, costs had to be kept under control. That is quite a list of objectives that Tesla needed to achieve in a very short time frame. Because of these objectives, some hiccups were encountered along the way, particularly in regard to delays in reaching production goals and cash flow concerns. Decision analysis would help to prioritize multiple objectives.

• Project managers deal with uncertainties. Predicting the future is not an easy task. Selecting alternatives is the primary objective of decision analysis. Decision analysis offers tools to help project managers deal with uncertainties.

• Project management problems can be complex. The number of alternatives you face in managing a project can be significant. Decisions are usually made sequentially, based on previous decisions. Moreover, understanding how each decision will affect subsequent ones is difficult.

• Most projects include multiple stakeholders. Project managers deal with clients, project team members, project sponsors, and subcontractors, among others. All these stakeholders have different objectives and preferences.

Decision Analysis as a Process

Having explained what decision analysis encompasses, we still must ask: What is it, really? First, decision analysis is a tool to solve problems. It is a “practical framework of methods and tools to promote creativity and help people make better decisions” (Keeney 1982).

As a project manager, you don’t need to know every last detail about these methods and tools, some of which can be extremely complicated. It is important, however, that you know two basic things that affect how decisions are made:

• We are all subject to common psychological pitfalls. People come hardwired with psychological constructs that can mislead them when they make project decisions. If you are estimating projects costs, identifying possible risks, selecting viable alternatives, or identifying the most important project objectives, you can make predictable mental mistakes. A basic knowledge of these pitfalls and how they can affect decision-making will help you avoid them.

• We can use decision analysis techniques to avoid those pitfalls. These techniques will improve your ability to make better decisions. Moreover, most of these techniques can be applied in other areas of practice, such as financial analysis.

What you really need to know in general is that project decision analysis is a scalable and flexible process that is both practical and effective. In addition, it is important to understand that decision analysis is not a process that creates an additional level of bureaucracy. It can be integrated into other processes that are defined in the PMBOK^® Guide (Project Management Institute 2018). We strongly recommend that you begin to establish this process by improving your own thinking processes rather than setting it up at the organizational level.

The process includes four major phases (which are discussed in the following parts of this book):

1. Decision-framing, or structuring the problem (Part 1)

2. Modeling the situation (Part 2)

3. Quantitative analysis (Part 3)

4. Implementation, monitoring, and reviews of the decisions (Part 4)

Each phase of the process involves several steps, which we will cover in our discussions of each phase.

Often, project managers believe that decision analysis is a type of cost-benefit analysis. That is a technique used to compare the various costs associated with a project with the benefits that it is intended to return. In comparison, decision analysis is a much broader process that takes into account many parameters and uncertainties. It focuses on developing a more complete analysis of a project and on understanding the ramifications of the possible choices facing a project manager.

Normative and Descriptive Decision Theory

The foundation of decision analysis is decision theory, which is the study of how to make better choices when faced with uncertainties. Normative decision theory describes how people should make decisions; descriptive decision theory describes how people actually make their decisions.

To distinguish between the normative and the descriptive approaches, let’s look at decisions related to recovering a hidden treasure. The movie National Treasure (2004), starring Nicolas Cage, follows a team of treasure hunters as they methodically and logically unravel a series of extremely convoluted clues. This is an example of normative decision theory, because it shows how people should behave if they want to recover a treasure. Stanley Kramer’s movie It’s a Mad, Mad, Mad World (1963) is an example of descriptive decision theory, for it shows how people actually behave when they try to recover a treasure. In trying to find the treasure, instead of acting logically, the characters behave spontaneously and irrationally. Chaos and hilarity ensue, yet no treasure is found.

Driving Forces behind Project Decision Analysis

Realizing that poor decision-making in large-scale projects can both result in high costs and even cause harm, governments and private businesses alike are increasingly recognizing the importance of instituting decision analysis techniques.

The U.S. Government Performance Results Act of 1993 states that “waste and inefficiency in Federal programs undermine the confidence of the American people in the Government and reduce the Federal Government’s ability to address adequately vital public needs.” The first stated purpose of the act is to “improve the confidence of the American people in the capability of the Federal Government, by systematically holding Federal agencies accountable for achieving program results.”

The act mandates that all major decisions made by government agencies be properly justified in the public interest. One of the main outcomes of the act is a much wider adoption of decision analysis and risk management in government organizations.

Private companies also understand the importance of decision analysis to justify their decisions. It is not enough for a company’s management to report to shareholders and Wall Street analysts that the company just spent X million dollars on research and development and Y million on capital projects. Investors need to see assurances that their money was spent wisely. Therefore, many companies have started to establish structured decision analysis processes. Many organizations use decision support tools such as Enterprise Resource Management or Project Portfolio Management systems to improve their efficiencies. SixSigma is a proven methodology to improve decision-making related to quality. One of the main areas of improvement, especially in the area of new product development, is the ability to successfully select which projects should go forward.

Government regulations and pressure from investors have become the driving forces behind the wider adoption of decision analysis. As government agencies and large companies implement the process, more information about decision analysis is becoming available, more experience with the technique is being accumulated, and more businesses are using it to improve the efficiencies of their projects.

A Little Bit of History

The fathers of decision analysis had lofty goals. In the 1700s, the French-born mathematician Abraham de Moivre and the English Presbyterian minister and mathematician Thomas Bayes tried to apply mathematics to prove the existence of God. Their work made important contributions to probabilities and statistics. In 1718, de Moivre published The Doctrine of Chances, in which he presented the concept of relative frequency for probabilities. De Moivre became one of the fathers of the “frequentistic” approach to the theory of probabilities and statistics. Bayes came up with a different concept, one that would later become the foundation for the Bayesian theory in the field of probabilities. Around the same time, a Swiss mathematician and physicist, Daniel Bernoulli, came up with idea of decision-making based on analyzing various possible outcomes of given events. Their work became the foundation of decision analysis.

The publication of Theory of Games and Economic Behavior in 1944, by John von Neumann and Oskar Morgenstern, was another significant step in decision science. After their theory was published, a number of scholars developed expansions and variations on it (Savage 1954; Luce 1959; Fishburn 1984; Karmarkar 1978; Payne 1973; Coombs 1975). Contemporary decision theory was introduced in the 1960s by Howard Raiffa and Robert Schlaifer of the Harvard Business School, who introduced the framework of decision analysis methods and tools (Raiffa 1968; Schlaifer 1969). The advent of the computer over the past few decades has also had a strong influence, and today decision and risk analysis software has become a useful tool for practitioners.

Interestingly, in 2002 the Nobel Prize for economics was awarded to a psychologist rather than an economist. Daniel Kahneman was awarded the prize for “having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty” (Sveriges Riksbank Prize 2002). The research, which Kahneman conducted with Amos Tversky and other psychologists, outlined the basic psychological foundation behind decision-making, which has significantly changed our understanding of human behavior. It affected not only our understanding of economics but also other areas, including project management. Kahneman later wrote a popular book called Thinking, Fast and Slow (Kahneman 2013), which is a comprehensive, easy-to-read overview of the psychology of judgment and decision-making as well as of Kahneman’s own research.

In 2017 Nobel Award in economics was awarded to Richard Thaler for his contribution to behavioral economics, which is directly related to decision analysis. Thaler is a professor of behavioral science and economics at the University of Chicago, Booth School of Business. In 2015, he served as president of the American Economic Association. He is probably most well-known for authoring, with Cass Sunstein, the best-selling book Nudge: Improving Decisions about Health, Wealth, and Happiness (Thaler and Sunstein 2009).

Decision Analysis Today

Built on the work of many scholars in numerous fields, decision analysis has now become a practical framework that helps to solve a huge variety of problems in various disciplines, including project management. The methodology is widely used by many companies—General Motors, DuPont, Boeing, Eli Lilly, AT&T, Exxon Mobil, Shell, Chevron, BP, Novartis, Baxter Bioscience, Bristol-Myers Squibb, and Johnson & Johnson, to name a few—as well as in U.S. government agencies such as the Department of Defense, Department of Homeland Security, and NASA. Because easy-to-use, decision analysis software tools have become widely available, the adoption of decision analysis methods in all types of organizations, even down to small- and medium-sized companies, has accelerated (see appendix A).

Many universities, including Stanford, Harvard, Duke, the London School of Economics and Political Science, University of California–Los Angeles, and the University of Massachusetts, offer courses in decision analysis. And a substantial number of scientific papers, textbooks, and reference works on the subject have been published in recent years.

Experts in decision analysis have joined together in a number of professional organizations, one being the Decision Analysis Society. That society is a subdivision of the Institute for Operations Research and the Management Sciences (INFORMS, for short). It publishes the journal Decision Analysis and holds group meetings in conjunction with INFORMS annual meetings. Another professional group, the Decision Analysis Affinity Group (DAAG), focuses mostly on practical aspects of decision analysis. The Society for Judgment and Decision-Making (SJDM) focuses mostly on the behavioral aspects of decision theory.