Engineering Decision Making and Risk Management

Textbook cover

Engineering Decision Making and Risk Management

Jeffrey W. Herrmann

A. James Clark School of Engineering, University of Maryland, College Park

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Engineering Decision Making and Risk Management (John Wiley and Sons, 2015) is a textbook for a course on decision making and risk management. It is designed for advanced undergraduates, graduate students, and professional engineers.

The text covers decision analysis techniques to improve decision making, with applications in engineering design and engineering management, the analysis of decision-making processes, risk management processes, and understanding and improving decision-making systems.

This textbook covers important topics on decision making, presents tools for helping engineers make better decisions, and provides examples to illustrate the concepts and techniques. Students and engineers who study this material and apply these concepts and techniques should become better decision-makers.

This text discusses three perspectives on decision making: (1) the problem-solving perspective, (2) the decision-making process perspective, and (3) the decision-making system perspective. Techniques for modeling and managing risk are included throughout the text where appropriate within this framework.

For students: Every chapter includes learning objectives that state what the reader will be able to do after studying the chapter and exercises for practicing the relevant skills. Every chapter cites books and papers that provide more details about the concepts and examples that were presented, give formal proofs of important results, and describe other related material. A list of references cited is provided at the end of every chapter. The strengths and weaknesses of the techniques are presented to indicate when each is most appropriate. The examples include both historical and contemporary events.

For instructors: Instructional support material will be available from the publisher for instructors who wish to teach a course in which the students learn the skills that are covered in this text. This material includes not only worked solutions to the exercises in the textbook but also daily lesson plans for lectures, in-class activities, slides, and spreadsheets.

Engineering Decision Making and Risk Management contains the following chapters:

  1. Introduction to Engineering Decision Making: This chapter discusses the characteristics of engineering decision making and describes three perspectives on decision making: (1) the problem-solving perspective, (2) the decision-making process perspective, and (3) the decision-making system perspective. It identifies problems that can occur in decision making and the benefits of improving decision making.
  2. Decision Making Fundamentals: This chapter reviews some fundamental topics, including the context of a decision situation, fundamental objectives and means objectives, influence diagrams, rationality, choice strategies, dominance, framing a decision situation, risk acceptance criteria, and types of measurement scales. Understanding these important fundamental concepts can help one improve decision making.
  3. Multicriteria Decision Making: This chapter covers multicriteria decision making, which is a traditional topic in decision analysis and an important skill that is the foundation of decision making. This chapter covers multiple techniques: the Pugh matrix, a version of the analytic hierarchy process (AHP), multiattribute utility theory (MAUT), and conjoint analysis. It also discusses the usefulness of the Value of a Statistical Life and the differences between compensating and non-compensating solutions.
  4. Group Decision Making: This chapter reviews techniques for group decision making. The chapter covers two primary techniques: ranking (including the Kemeny-Young method) and scoring, including the majority judgment technique. It also discusses the implications of Arrow's Impossibility Theorem.
  5. Decision Making Under Uncertainty: This chapter introduces decisions with uncertainty (risky decisions) and includes traditional material on decision trees, risk aversion, and expected utility. It discusses different types of uncertainties and subjective probabilities. It also defines different types of robustness measures and presents uncertainty propagation techniques, including sensitivity analysis, the method of moments, and Monte Carlo simulation.
  6. Game Theory: The existence of another decision-maker introduces uncertainty, and this chapter discusses two-player simultaneous, zero-sum games (and finding optimal mixed strategies), two-player, simultaneous, mixed-motive games, and two-player Stackelberg games. Game theory is also useful for considering risks due to intelligent adversaries.
  7. Decision-making Processes: This chapter reviews many types of useful decision-making processes, the important roles of heuristics and search in decision making, and the composite nature of decisions. It also discusses the secretary problem, a special case in which the decision-making process can be optimized. This chapter also describes product development as a type of decision-making process.
  8. The Value of Information: This chapter discusses the value of information. This chapter describes how to calculate the expected value of perfect information and the expected value of imperfect information and discusses more generally how to use experimental information to improve decision making.
  9. Risk Management: This chapter covers the process of risk management, which includes the decision of which risk mitigation activity (or activities) should be performed. Risk management is a type of decision-making process. This chapter describes different risk management processes and risk communication. This chapter discusses poor decisions and how to learn from those that do occur.
  10. Decision-making Systems: This chapter describes the characteristics and structure of decision-making systems, including different roles and mechanisms of organizational influence. It also describes product development organizations as decision-making systems. This chapter considers the flow of information between different decision-makers who have different roles.
  11. Modeling and Improving Decision-making Systems: This chapter discusses improving decision-making systems. Because decision-making systems are complex and involve human actors, the usefulness of quantitative techniques is limited. Qualitative approaches can represent more interesting phenomena. The chapter begins with different techniques for modeling decision-making systems, including rich pictures, swimlanes, root definitions, and conceptual models. The chapter also presents an improvement strategy that exploits the insights that these types of models provide.

This page last updated on February 6, 2016.