Engineering Decision Making and Risk Management E-Book

Jeffrey W. Herrmann

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Veröffentlichungsjahr: 2015

Beschreibung

IIE/Joint Publishers Book of the Year Award 2016!

Awarded for ‘an outstanding published book that focuses on a facet of industrial engineering, improves education, or furthers the profession’.

Engineering Decision Making and Risk Management emphasizes practical issues and examples of decision making with applications in engineering design and management

Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems.

Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision-making systems, Engineering Decision Making and Risk Management also features:

• Theoretically sound and practical tools for decision making under uncertainty, multi-criteria decision making, group decision making, the value of information, and risk management
• Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes
• End-of-chapter exercises for readers to apply specific learning objectives and practice relevant skills
• A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in-class activities, slides, and spreadsheets

An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics.

Leseprobe

Table of Contents

Cover

Title Page

Copyright

Dedication

Preface

Chapter 1: Introduction to Engineering Decision Making

1.1 Introduction

1.2 Decision Making in Engineering Practice

1.3 Decision Making and Optimization

1.4 Decision Making and Problem Solving

1.5 Decision Making and Risk Management

1.6 Problems in Decision Making

1.7 The Value of Improving Decision Making

1.8 Perspectives on Decision Making

Exercises

References

Chapter 2: Decision-Making Fundamentals

2.1 Decision Characteristics

2.2 Objectives in Decision Making

2.3 Influence Diagrams

2.4 Rationality

2.5 Dominance

2.6 Choice Strategies

2.7 Making Tradeoffs

2.8 Reframing the Decision

2.9 Risk Acceptance

2.10 Measurement Scales

Exercises

References

Chapter 3: Multicriteria Decision Making

3.1 Pugh Concept Selection Method

3.2 Analytic Hierarchy Process

3.3 Multiattribute Utility Theory

3.4 Conjoint Analysis

3.5 Value of A Statistical Life

3.6 Compensation

3.7 The Impact of Changing Weights

Exercises

References

Chapter 4: Group Decision Making

4.1 Ranking

4.2 Scoring and Majority Judgment

4.3 Arrow's Impossibility Theorem

Exercises

References

Chapter 5: Decision Making Under Uncertainty

5.1 Types of Uncertainties

5.2 Assessing a Subjective Probability

5.3 Imprecise Probabilities

5.4 Cumulative Risk Profile and Dominance

5.5 Decision Trees: Modeling

5.6 Decision Trees: Determining Expected Values

5.7 Sequential Decision Making

5.8 Modeling Risk Aversion

5.9 Robustness

5.10 Uncertainty Propagation: Sensitivity Analysis

5.11 Uncertainty Propagation: Method of Moments

5.12 Uncertainty Propagation: Monte Carlo Simulation

Exercises

References

Chapter 6: Game Theory

6.1 Game Theory Basics

6.2 Zero-Sum Games

6.3 Optimal Mixed Strategies for Zero-Sum Games

6.4 The Minimax Theorem

6.5 Resource Allocation Games

6.6 Mixed Motive Games

6.7 Bidding

6.8 Stackelberg Games

Exercises

References

Chapter 7: Decision-Making Processes

7.1 Decision-Making Contexts

7.2 Technical Knowledge and Problem Consensus

7.3 Optimization: Search and Evaluation

7.4 Diagnosing Risk Decision Situations

7.5 Values and Ethics

7.6 Systematic Decision-Making Processes

7.7 The Decision-Making Cycle

7.8 The Analytic-Deliberative Process

7.9 Concept Selection

7.10 Decision Calculus

7.11 Recognition-Primed Decision Making

7.12 Heuristics

7.13 Unconscious Decision Making

7.14 Search

7.15 Types of Search in Practice

7.16 Secretary Problem

7.17 Composite Decisions

7.18 Separation

7.19 Product Development Processes

Exercises

References

Chapter 8: The Value of Information

8.1 The Expected Value of Perfect Information

8.2 The Expected Value of Imperfect Information

8.3 Experimentation to Reduce Ambiguity

8.4 Experimentation to Compare Alternatives

8.5 Experimentation to Compare Alternatives with Multiple Attributes

Exercises

References

Chapter 9: Risk Management

9.1 Risk Management Process

9.2 Potential Problem Analysis

9.3 Risk Management Guide for DOD Acquisition

9.4 Risk Management at NASA

9.5 Precursors

9.6 Warnings

9.7 Risk Communication

9.8 Managing The Risk of A Bad Decision

9.9 Learning From Failures

9.10 Transforming Failure Information

Exercises

References

Chapter 10: Decision-Making Systems

10.1 Introduction to Decision-Making Systems

10.2 Mechanisms of Organization Influence

10.3 Roles in Decision-Making Systems

10.4 Information Flow

10.5 The Structure of Decision-Making Systems

10.6 Product Development Organizations

10.7 Information Flow in Product Development

10.8 The Design Factory

Exercises

References

Chapter 11: Modeling and Improving Decision-Making Systems

11.1 Modeling Decision-Making Systems

11.2 Rich Pictures

11.3 Swimlanes

11.4 Root Definitions

11.5 Conceptual Models

11.6 Models of Product Development Organizations

11.7 Improving Decision-Making Systems

11.8 An Integrative Strategy

Exercises

References

Index

End User License Agreement

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Guide

Cover

Table of Contents

Preface

Begin Reading

List of Illustrations

Figure 2.1

Figure 2.2

Figure 2.3

Figure 2.4

Figure 2.5

Figure 2.6

Figure 2.7

Figure 3.1

Figure 4.1

Figure 5.1

Figure 5.2

Figure 5.3

Figure 5.4

Figure 5.5

Figure 5.6

Figure 5.7

Figure 5.8

Figure 6.1

Figure 6.2

Figure 6.3

Figure 6.4

Figure 6.5

Figure 6.6

Figure 6.7

Figure 7.1

Figure 7.2

Figure 7.3

Figure 7.4

Figure 7.5

Figure 7.6

Figure 7.7

Figure 8.1

Figure 8.2

Figure 8.3

Figure 8.4

Figure 8.5

Figure 8.6

Figure 8.7

Figure 8.8

Figure 8.9

Figure 8.10

Figure 8.11

Figure 8.12

Figure 9.1

Figure 9.2

Figure 9.3

Figure 9.4

Figure 9.5

Figure 9.6

Figure 9.7

Figure 9.8

Figure 9.9

Figure 9.10

Figure 9.11

Figure 10.1

Figure 10.2

Figure 11.1

Figure 11.2

Figure 11.3

Figure 11.4

Figure 11.5

Figure 11.6

Figure 11.7

Figure 11.8

Figure 11.9

List of Tables

Table 2.1

Table 2.2

Table 2.3

Table 2.4

Table 3.1

Table 3.2

Table 3.3

Table 3.5

Table 3.6

Table 3.7

Table 3.8

Table 3.9

Table 3.10

Table 3.11

Table 3.12

Table 3.13

Table 3.14

Table 3.15

Table 3.16

Table 4.1

Table 4.2

Table 4.3

Table 4.4

Table 4.5

Table 4.6

Table 5.1

Table 5.2

Table 6.1

Table 7.1

Table 7.2

Table 8.1

Table 8.2

Table 8.3

Table 8.4

Table 9.1

Engineering Decision Making and Risk Management

Jeffrey W. Herrmann

A. James Clark School of Engineering

University of Maryland

College Park, Maryland

Copyright © 2015 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New Jersey

Published simultaneously in Canada

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, [phone], fax [phone], or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, [phone], fax [phone], or online at http://www.wiley.com/go/permissions.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

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Library of Congress Cataloging-in-Publication Data:

Herrmann, Jeffrey W.

Engineering decision making and risk management / Jeffrey W. Herrmann.

pages cm

Includes bibliographical references and index.

ISBN 978-1-118-91933-0 (hardback)

1. Engineering–Decision making. 2. Decision making. 3. Risk management. I. Title.

TA190.H467 2015

620.0068$′4–dc23

2014041070

Cover image: iStockphoto © MaximGostev

To L.G.H. and C.R.H.

Preface

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.

Like the products and systems that engineers design, this textbook began as an idea for meeting a need and went through many iterations and revisions over time. In this case, the initial discussions about engineering decision making involved my colleague Linda Schmidt, an expert on design methodologies and design education. She and I discussed how engineers in product development organizations shared information and made decisions, and we decided to begin studying this activity as a system. Then, with our colleague Peter Sandborn, we were awarded a grant from the National Science Foundation to study how firms used information about environmental impacts in product development decision making. After studying multiple firms and publishing our results, the next step was to develop a course in which we could share our insights about decision making with others. We jointly developed a course outline, and in the Spring, 2004, semester I taught the course for the first time. Although a traditional decision analysis textbook was used, the course included topics beyond its scope, so I created course notes and expanded them every time I taught the course.

In the meantime, our research continued, and I developed three perspectives on decision making. This led me to reorganize the course (and the course notes) around these three perspectives, which provide a new way to consider engineering decision making. In addition, I included various topics on risk management, a type of decision-making process. These changes also emphasized the challenges of using a traditional decision analysis textbook that was organized in a completely different way. The organization of this course was not increasing mathematical difficulty but increasing conceptual complexity, and existing texts on decision analysis were inappropriate. The first draft of this textbook was my reorganized set of course notes, which I then divided and rearranged again to form distinct chapters.

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. The text introduces these perspectives in Chapter 1 and covers them in sequence as the following paragraphs describe. Techniques for modeling and managing risk are included throughout the text where appropriate within this framework.

Chapters 2-6 consider the components and structure of decisions, which is the problem-solving perspective. Chapter 2 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.

After Chapter 2 are two chapters about decisions without uncertainty (Chapters 3 and 4) and then two chapters about decisions with uncertainty (Chapters 5 and 6).

Chapter 3 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.

Chapter 4 reviews techniques for group decision making. This material follows multicriteria decision making (Chapter 3) because the decisions do not have uncertainty. 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.

Chapter 5 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. (Other approaches for making decisions in the presence of uncertainty are discussed in Chapter 7.)

Chapter 6 then discusses game theory. This chapter is placed after Chapter 5 because the existence of another decision-maker introduces uncertainty, but this uncertainty is quite different from uncertainties that can be represented as random variables (which are discussed in Chapter 5). The 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.

Chapters 7-9 discuss the decision-making process perspective: how people make decisions through decision-making and risk management processes. Because different situations require different types of decision-making processes, Chapter 7 begins this part of the text by reviewing 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.

Chapter 8 discusses the value of information, a traditional topic. The decision to gather more information is usually a decision with uncertainty, but it is included in this part of the text because it is a decision about what to do in the decision-making process. 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.

Chapter 9 explicitly covers the process of risk management, which includes the decision of which risk mitigation activity (or activities) should be performed. The risk mitigation decision is another decision with uncertainty, but this material is included in this part of the text because risk management is a type of decision-making process, and Chapter 9 describes different risk management processes and risk communication, an important part of any decision-making process. Because choosing an appropriate decision-making process reduces the risk of making a poor decision, Chapter 9 discusses poor decisions and how to learn from those that do occur. Finally, because some risk management processes emphasize continuously monitoring an activity and intervening when needed to reduce risk, these processes can be viewed as a control system. This means that the risk management function is also a decision-making system, which is the third perspective.

In the last part of the text, Chapters 10 and 11 describe the decision-making characteristics of organizations and how to improve those decision-making systems, which is relevant to the decision-making system perspective. This perspective considers the flow of information between different decision-makers who have different roles. It views an organization as a dynamic system that makes decisions using decision-making processes, but the quality of the decisions that emerge depends upon not only the decision-making processes but also the culture and the patterns of behavior.

Chapter 10 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.

Chapter 11 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.

Thus, the text begins with the aspect of decision making that is, conceptually, the simplest: given a set of alternatives and a decision-maker's preferences, which one should be selected? The text then looks “behind the scenes,” so to speak, to describe the processes used to generate and evaluate the alternatives. Finally, the text “steps back” to look at the organization that, to achieve its goals, performs these processes and makes these decisions.

In the first part of the text (Chapters 2-6), the critical skill is choosing the right alternative. In the second part (Chapters 7-9), the critical skill is executing the right decision-making process. In the third part (Chapters 10 and 11), the critical skill is improving the decision-making system.

The content and organization of this text reflect both a pragmatic attitude about improving decision making and the scholarly concern with studying, organizing, and formalizing this activity. This approach has been formed by studying how engineers and others decide, using the quantitative, analytical techniques that are available, and helping others become better decision-makers. This text follows the view that the mathematical models used in the study of decision making, no matter how sophisticated, are merely approximations of what the mysterious human mind does and what complex human organizations accomplish. Thus, they are valuable if they are useful to those who need to make decisions. The text, therefore, includes a variety of models that have been generally useful. In some cases the numbers that using such a model produces may be less valuable than the conversations and negotiations that are required to construct the model. At the same time, studies of how people decide in practice have revealed that formal techniques are used less often than informal, intuitive rules or heuristics. Understanding this is valuable, of course, but improving decision-making requires learning how and when to use formal techniques as well.

The text's diversity may concern any who are committed to a single approach to the study of decision making, but I hope that they will see how each approach is an important part of a valuable perspective on decision-making. The organization of the text (around the three perspectives) provides a synthesis that places different approaches and techniques in relationship to each other, which is an important scholarly and pedagogical task.

The contents of the text will reveal the influence of many scholars, including those who have developed traditional decision analysis and those who have studied how people decide in practice. The work of Herb Simon has influenced the material greatly. His insights into how engineers design, how people solve problems, and how organizations make decisions have influenced the choice of material and the discussions in this text. His proposals for a curriculum in design remain relevant today. His descriptions of administrative behavior provide valuable, applicable insights for engineers, who must work with others in organizations. This text directly addresses his observation that an organization is a decision-making system. Simon wrote that creating the right representation of a problem makes the solution clear; this text takes up that challenge by describing multiple ways to represent decision making. The three perspectives discussed in this text are representations of decision making, and those who seek to improve their decision-making skills and choose an appropriate perspective will find promising opportunities. This text is intended to help develop an “intellectually tough, analytic, partly formalizable, partly empirical, teachable doctrine” (in Simon's words).

Although this text focuses on engineers, decision making occurs everywhere and is especially relevant in other professions that require selecting a possible solution from many alternatives. This includes architecture, law, and medicine, among many others. Of course, this text, which also reflects the preferences of the author and is bounded, cannot include every known technique. In particular, human cognition, behavioral decision making, introductory probability and statistics, optimization, advanced game theory, risk assessment, and decision support system design are beyond the scope of this textbook. Excellent texts on these topics are already available.

The text is designed for advanced undergraduates, graduate students, and engineering professionals who are comfortable with logical reasoning, calculation, probability, mathematics, and optimization, but it does not require advanced theoretical mathematics. Although students may have little experience with “real-world” engineering decisions that have large stakes, they make many decisions, and investing the time to study and improve decision making early will yield benefits throughout their careers.

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 interesting and useful 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. Many of the papers cited can be found in online journals and databases and accessed via the Internet; others can be obtained through a university library. Most of the books can be found in libraries and bookstores everywhere.

Because the organization of this textbook does not follow the outline of most decision analysis texts, it may be out of place as a primary text for a traditional decision analysis course. It could be used as a secondary or supplementary text in such a course.

Thus, to help an instructor who wishes to teach a course in which the students learn the skills that are covered in this text, it seemed appropriate to develop and provide instructional support material that includes not only worked solutions to the exercises in the textbook but also daily lesson plans for lectures, in-class activities, slides, and spreadsheets for a course that covers engineering decision making and risk management. These materials are available from the publisher.

While conducting the study of decision making that has led to this text, I have been greatly influenced, encouraged, and assisted by my colleagues, including Linda Schmidt, Joseph Donndelinger, and Erica Gralla, and my students, including Peyman Karimian and Dennis Leber. Some of the material discussed in this text previously appeared in various papers that I and my collaborators have written, but all of the chapters are original.

Chapter 1Introduction to Engineering Decision Making

Learning Objectives:

After studying this chapter, the reader will be able to do the following:

Identify and describe two types of decisions that engineers make (Section 1.2).

Classify the decisions that engineers make (Section 1.2).

Describe how optimization is related to decision making (Section 1.3).

Describe how problem solving is related to decision making (Section 1.4).

Explain why decision making is part of risk management (Section 1.5).

Identify problems that can occur in decision making (Section 1.6).

Identify the benefits of improving decision making (Section 1.7).

Describe a decision from three perspectives (Section 1.8).

1.1 Introduction

Why should engineers study decision making? What is engineering decision making?

People have always made decisions, but analyzing decision-making processes and developing better decision-making methods are more recent activities. Our ability to analyze decisions has increased as mathematics, especially the theory of probability, has developed. In the 1700s, Daniel Bernoulli analyzed risky decisions and described how the relative values of alternatives depend on the preferences of the decision maker (Bernoulli, 1954). Ramsey (1964) developed a theory for decision making based on probability theory and utility. von Neumann and Morgenstern (1944) formalized the theory of expected utility and the analysis of multiplayer games, which is now known as game theory. Early works on game theory include Borel (1921), von Neumann (1928, 1959), and Hotelling (1929), who analyzed a game related to product differentiation. The works of Savage (1954), Raiffa (1968), Schlaifer (1969), Benjamin and Cornell (1970), and Keeney and Raiffa (1976) have been cited as influential early textbooks. Buchanan and O'Connell (2006) surveyed the history of decision making and the roles of intuition, risk, groups, and computing in decision making.