Project Decisions

Lev Virine, Michael Trumper

• Publisher: Berrett-Koehler Publishers
• Year: 2007
• ISBN:
  9781567263923
• Edition: 1
• Topic: Business
• Subtopic: Organisational Behaviour
• Index: Business

Project management is the art of making the right decisions. To be effective as a project manager, you must know how to make rational choices in project management, what processes can help you to improve these choices, and what tools are available to help you through the decision-making process. Project Decisions: The Art and Science is an entertaining and easy-to-read guide to a structured project decision analysis process. This valuable text presents the basics of cognitive psychology and quantitative analysis methods to help project managers make better decisions. Examples that portray different projects, real-life stories, and popular culture will help readers acquire the essential knowledge and skills required for effective project decision-making. Readers will be able to:
•Understand psychological pitfalls related to project management
•Establish a creative business environment in their organization
•Identify project risks and uncertainties
•Develop estimates of project time and cost based on an understanding of human psychology
•Perform basic quantitative and qualitative risk and decision analysis
•Use event chain methodology in managing projects
•Communicate the results of decision analysis to decision-makers
•Review project decisions and perform adaptive project management
•Establish a project decision analysis process in their organizationPLUS — Test your own judgment through a quiz that examines your intuition!

PART 1

Introduction to Project Decision Analysis

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 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, 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 to stop and restart work on the foundations for the tower that will support the suspension span. State funds and increased toll revenue (tolls were raised to $4) from state-owned bridges would cover the burden of the cost overrun from the governor’s costly decision to delay the project.

Wrong decisions are a burden that we impose on each other.

Figure 1.1 The New Bay Bridge

If you don’t live in northern California, you may not be directly affected by the Bay Bridge cost overrun. But, 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 taxes.

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

Problems result from poor decision-making, whether the decision-maker is the manager at the pharmaceutical company, the geologist making a poor choice of where to drill for oil, the ineffective government bureaucrat or legislator making policy for the wrong reasons, or even you 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 multibillon-dollar oil pipeline but make a wrong decision about running it through a particular location. Then we 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.

Annually, 44,000 to 98,000 deaths occur due to medical errors (Kohn, Corrigan, and Donaldson 2000). That number would represent approximately 1.8 to 4.0 percent of the 2.4 million deaths that the Centers for Disease Control (CDC) reported in 1999. As a point of comparison for other causes of death, the CDC also reported that in 1999 there were 68,399 deaths from diabetes, 63,730 from influenza and pneumonia, and 44,536 from Alzheimer’s disease. A 2004 study (Adams 2004) put the number much higher, at 195,000 people killed each year in U.S. hospitals due to medical errors.

Similar figures on the impact of poor decision-making are available from the oil industry (Rose 2001). An exploratory well drilled some distance from an existing field is called a wildcat. A wildcat chance represents the ratio of oil and gas discoveries to wildcats (Table 1.1).

Exploratory drilling is always a risky business. Nevertheless, the wildcat chance can be improved by making better decisions: for example, by avoiding an incorrect interpretation of geological data, which was the primary source of dry holes in more than 40 percent of cases (Rose 2001). Even a slight improvement in the process of deciding where to drill wildcats would have significant economic benefits because drilling a well can cost millions of dollars.

Table 1.1 Global Discoveries (excludes U.S. and Canada)

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 and Wright 2004). 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 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. But 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. Plus, there are many alternatives. Now, relying solely on your intuition may not be enough; you probably should perform a decision analysis.

Why is decision-making so complicated? There are a number of reasons:

Most problems in project management involve multiple objectives (Goodwin and Wright 2004). An example of a project with multiple conflicting objectives is General Motors’s EV1 electric-car program. The car was introduced in 1997 to demonstrate GM’s corporate commitment to a clean environment and at the same time show the commercial viability of the technology (GM 2006). But GM pulled the plug on the project in 2002, citing insufficient public support. The automaker eventually collected and destroyed almost all of the 1,000 EV1 cars, prompting ...