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| decision analysis for the professional: Decision Analysis for the Professional Peter McNamee, John Celona, 2001 |
| decision analysis for the professional: Handbook of Decision Analysis Gregory S. Parnell, Terry Bresnick, Steven N. Tani, Eric R. Johnson, 2013-01-24 A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and modeling. Readers will learn how to identify and overcome the numerous challenges of decision making, choose the appropriate decision process, lead and manage teams, and create value for their organization. Performing modeling analysis, assessing risk, and implementing decisions are also addressed throughout. Additional features include: Key insights gleaned from decision analysis applications and behavioral decision analysis research Integrated coverage of the techniques of single- and multiple-objective decision analysis Multiple qualitative and quantitative techniques presented for each key decision analysis task Three substantive real-world case studies illustrating diverse strategies for dealing with the challenges of decision making Extensive references for mathematical proofs and advanced topics The Handbook of Decision Analysis is an essential reference for academics and practitioners in various fields including business, operations research, engineering, and science. The book also serves as a supplement for courses at the upper-undergraduate and graduate levels. |
| decision analysis for the professional: Decision Analysis for Management Judgment Paul Goodwin, George Wright, 2014-05-12 Decision Analysis for Management Judgment is unique in its breadth of coverage of decision analysis methods. It covers both the psychological problems that are associated with unaided managerial decision making and the decision analysis methods designed to overcome them. It is presented and explained in a clear, straightforward manner without using mathematical notation. This latest edition has been fully revised and updated and includes a number of changes to reflect the latest developments in the field. |
| decision analysis for the professional: Introduction to Decision Analysis David C. Skinner, 2009 This book is the most practical and thought-provoking step-by-step guide to making better decisions that is available today! Proven techniques and solid experience are the foundation for this classic text, which was written for the manager and for the decision analysis practitioner!-- |
| decision analysis for the professional: Foundations of Decision Analysis Ronald A. Howard, Ali El-Sayed Abbas, 2015-01-21 For courses in Decision Making and Engineering. The Fundamentals of Analyzing and Making Decisions Foundations of Decision Analysis is a groundbreaking text that explores the art of decision making, both in life and in professional settings. By exploring themes such as dealing with uncertainty and understanding the distinction between a decision and its outcome, the First Edition teaches readers to achieve clarity of action in any situation. The book treats decision making as an evolutionary process from a scientific standpoint. Strategic decision-making analysis is presented as a tool to help students understand, discuss, and settle on important life choices. Through this text, readers will understand the specific thought process that occurs behind approaching any decision to make easier and better life choices for themselves. |
| decision analysis for the professional: Multi-objective Decision Analysis Clinton W. Brownley, 2013-03-28 Whether managing strategy, operations or products, knowing how to make the best decision in a complex, uncertain business environment is difficult. You might be faced with multiple, competing objectives, which means making trade-offs. To complicate matters, any uncertainty makes it hard to explicitly understand how different objectives will impact potential outcomes. This book will help you face these problems. It provides a decision analysis framework implemented as a simple spreadsheet tool. This multi-objective decision analysis framework helps you to measure trade-offs among objectives and incorporate uncertainties and risk preferences. With this book, you will be able to identify what information is needed to make a decision, define how that information should be combined, and, finally, provide quantifiable evidence to clearly communicate and justify the decision. The process involves minimal overhead and is perfect for busy professionals who need a simple, structured process for making, tracking, and communicating decisions. This process makes decision making more efficient by focusing only on information and factors that are well-defined, measureable, and relevant to the decision at hand. The framework requires clear characterization of a decision, ensuring that it can be traced and is consistent with the intended objectives and organizational values. Using this structured decision-making framework, anyone can consistently make better decisions to gain competitive and strategic advantage. |
| decision analysis for the professional: Decision Synthesis Stephen R. Watson, Dennis M. Buede, 1987 Offers a comprehensive overview of the theory of decision making and its practical application in decision analysis. |
| decision analysis for the professional: Problem Solving, Decision Making, and Professional Judgment Paul Brest, Linda Hamilton Krieger, 2010-05-26 In Problem Solving, Decision Making, and Professional Judgment, Paul Brest and Linda Hamilton Krieger have written a systematic guide to creative problem solving that prepares students to exercise effective judgment and decision making skills in the complex social environments in which they will work. The book represents a major milestone in the education of lawyers and policymakers, Developed by two leaders in the field, this first book of its type includes material drawn from statistics, decision science, social and cognitive psychology, the judgment and decision making (JDM) literature, and behavioral economics. It combines quantitative approaches to empirical analysis and decision making (statistics and decision science) with the psychological literature illustrating the systematic errors of the intuitive decision maker. The book can stand alone as a text or serve as a supplement to a core law or public policy curriculum. Problem Solving, Decision Making, and Professional Judgment: A Guide for Lawyers and Policymakers prepares students and professionals to be creative problem solvers, wise counselors, and effective decision makers. The authors' ultimate goals are to help readers get it right in their roles as professionals and citizens, and to arm them against common sources of judgment error. |
| decision analysis for the professional: Clinical Decision Analysis Milton C. Weinstein, Harvey V. Fineberg, 1980 |
| decision analysis for the professional: Business Decision Analysis Graham Hackett, Peter Luffrum, 1999-06-18 Business Decision Analysis is part of a major new national programme of texts and modules designed for undergraduate students on Business Studies degree courses. It provides 150 hours of high quality study to be used in a supported learning environment. The module provides a comprehensive introduction to the quantitative analysis and solution of business problems and covers some of the key topics in the field, including an introduction to model building for business decision analysis, linear programming, regression analysis, time-series analysis and simulation techniques. Business Decision Analysis contains numerous activities and exercises to develop an understanding of the subject, including many utilizing Microsoft Excel in version 5.0 or later (not supplied with this publication). The module provides the most effective teaching and learning resource available at this level. |
| decision analysis for the professional: Modern Methods of Clinical Investigation Institute of Medicine, Committee on Technological Innovation in Medicine, 1990-02-01 The very rapid pace of advances in biomedical research promises us a wide range of new drugs, medical devices, and clinical procedures. The extent to which these discoveries will benefit the public, however, depends in large part on the methods we choose for developing and testing them. Modern Methods of Clinical Investigation focuses on strategies for clinical evaluation and their role in uncovering the actual benefits and risks of medical innovation. Essays explore differences in our current systems for evaluating drugs, medical devices, and clinical procedures; health insurance databases as a tool for assessing treatment outcomes; the role of the medical profession, the Food and Drug Administration, and industry in stimulating the use of evaluative methods; and more. This book will be of special interest to policymakers, regulators, executives in the medical industry, clinical researchers, and physicians. |
| decision analysis for the professional: Multi-criteria Decision Analysis Alessio Ishizaka, Philippe Nemery, 2013-06-10 This book presents an introduction to MCDA followed by more detailed chapters about each of the leading methods used in this field. Comparison of methods and software is also featured to enable readers to choose the most appropriate method needed in their research. Worked examples as well as the software featured in the book are available on an accompanying website. |
| decision analysis for the professional: Portfolio Decision Analysis Ahti Salo, Jeffrey Keisler, Alec Morton, 2011-08-12 Portfolio Decision Analysis: Improved Methods for Resource Allocation provides an extensive, up-to-date coverage of decision analytic methods which help firms and public organizations allocate resources to 'lumpy' investment opportunities while explicitly recognizing relevant financial and non-financial evaluation criteria and the presence of alternative investment opportunities. In particular, it discusses the evolution of these methods, presents new methodological advances and illustrates their use across several application domains. The book offers a many-faceted treatment of portfolio decision analysis (PDA). Among other things, it (i) synthesizes the state-of-play in PDA, (ii) describes novel methodologies, (iii) fosters the deployment of these methodologies, and (iv) contributes to the strengthening of research on PDA. Portfolio problems are widely regarded as the single most important application context of decision analysis, and, with its extensive and unique coverage of these problems, this book is a much-needed addition to the literature. The book also presents innovative treatments of new methodological approaches and their uses in applications. The intended audience consists of practitioners and researchers who wish to gain a good understanding of portfolio decision analysis and insights into how PDA methods can be leveraged in different application contexts. The book can also be employed in courses at the post-graduate level. |
| decision analysis for the professional: Risk Assessment and Decision Analysis with Bayesian Networks Norman Fenton, Martin Neil, 2012-11-07 Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software. |
| decision analysis for the professional: Professional Judgment Jack Dowie, Arthur Elstein, 1988-01-14 Policy-capturing models, data-based aids, expert systems and decision analysis are the main decision-making techniques introduced here, with attention to their methodological bases and practical evaluation. |
| decision analysis for the professional: Decisions Under Uncertainty Ian Jordaan, 2005-04-07 Publisher Description |
| decision analysis for the professional: Decision Making Process Denis Bouyssou, Didier Dubois, Henri Prade, Marc Pirlot, 2013-05-10 This book provides an overview of the main methods and results in the formal study of the human decision-making process, as defined in a relatively wide sense. A key aim of the approach contained here is to try to break down barriers between various disciplines encompassed by this field, including psychology, economics and computer science. All these approaches have contributed to progress in this very important and much-studied topic in the past, but none have proved sufficient so far to define a complete understanding of the highly complex processes and outcomes. This book provides the reader with state-of-the-art coverage of the field, essentially forming a roadmap to the field of decision analysis. The first part of the book is devoted to basic concepts and techniques for representing and solving decision problems, ranging from operational research to artificial intelligence. Later chapters provide an extensive overview of the decision-making process under conditions of risk and uncertainty. Finally, there are chapters covering various approaches to multi-criteria decision-making. Each chapter is written by experts in the topic concerned, and contains an extensive bibliography for further reading and reference. |
| decision analysis for the professional: Bayesian Decision Analysis Jim Q. Smith, 2010-09-23 Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem, how data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years, all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics. |
| decision analysis for the professional: Business Statistics for Contemporary Decision Making Ignacio Castillo, Ken Black, Tiffany Bayley, 2023-05-08 Show students why business statistics is an increasingly important business skill through a student-friendly pedagogy. In this fourth Canadian edition of Business Statistics For Contemporary Decision Making authors Ken Black, Tiffany Bayley, and Ignacio Castillo uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today's workplace. |
| decision analysis for the professional: Decision Making Under Uncertainty Mykel J. Kochenderfer, 2015-07-24 An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines. |
| decision analysis for the professional: GIS and Multicriteria Decision Analysis Jacek Malczewski, 1999-04-05 From selecting sites for new hospitals, schools, and factories, to managing forests and rivers, to creating and maintaining highways and bridges, public and private organizations are often called on to make decisions on geographic questions that involve a multitude of alternatives and often conflicting evaluation criteria. This book presents a formal mechanism for dealing with these situations, capturing the information in a Geographic Information System and processing it to derive optimal recommendations for confronting these complex questions. |
| decision analysis for the professional: Risk Assessment and Decision Analysis with Bayesian Networks Norman Fenton, Martin Neil, 2018-09-03 Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course. |
| decision analysis for the professional: Risk and Decision Analysis in Projects John R. Schuyler, 2018-08-21 Decision analysis (DA) guides executives toward logical, consistent decisions under uncertainty. This book instructs readers in applying DA to feasibility analysis, project estimation, and project risk management.This is a wholly rewritten and expanded successor to the best-selling first and second editions.The entire investment lifecycle is covered, from conception, to the project plan, to the post-project review, and to a look-back analysis of the capital investment decision.DA applies to all manner of project management (PM) decisions for individuals, government, and non-profit organizations. The book uses a business investment perspective and assumes that maximizing value for the project owner is the objective.DA is a problem-solving process. There are four key features: 1) probabilities and probability distributions express best judgments about risks and uncertainties. 2) The organization has a decision policy expressed as a single metric (the objective function). 3) Probabilities and outcome values combine in the probability-weighting expected value calculation. 4) The organization as a policy to choose the best expected value alternative.This book aims to make decision making clear, simple, and logical. A clear decision policy can be elusive, and the author offers suggestions for making trade-offs among conflicting objectives. Converting the three pillars of project management (cost, schedule, and performance) into project value equivalents makes the trade-offs clear.This book is intended for serious PM students and practitioners. This is an essential concepts and how-to book. The scope is quantitative analysis, from project inception to post-project review. Project cost and schedule modeling, in modest detail, is essential to feasibility analysis and risk management. A general background in PM and corporate planning will be helpful. The methods are quantitative and straightforward. The reader should be comfortable with basic algebra and Microsoft(r) Excel(r).The book has eight pages of Suggested Reading annotated references (plus footnote additions), over 250 figures, approximately 600 Glossary definitions, and over 2400 Index entries. Online supplements include several whitepapers and other documents, example calculation spreadsheets, detailed color images of several important figures, four videos (including a critical chain simulation), and the Utility Elicitation Program (a web app, free for most users).Key topics include: Decision trees and Monte Carlo simulation for calculating outcome distributions and expected values * Probability concepts, including Bayes' rule for value of information analysis * Popular probability distribution types and when they apply * Eliciting expert judgments, with attention to potential cognitive and motivational biases * Recognizing the three pillars project in terms of project value * A 10-step decision analysis process * Project modeling concepts and techniques, with special attention to risk drivers and other correlations * Deterministic and stochastic sensitivity analysis * Decision policy that distinguishes objectives, time value, and risk attitude * @RISK(r) with Microsoft(r) Project for project simulations under uncertainty * Logical, consistent risk policy expressed as a utility function * Merge bias when task chains converge at a merge point * Tail estimate bias when estimating highly uncertain quantities * Optimizer's curse, a portfolio forecasting bias * Winner's curse, a bias characteristic of auctions * Using the best of critical chain and Monte Carlo simulation * Stochastic variance between a deterministic and a stochastic model * Modeling risk and uncertainty using probabilities, probability distributions, explicit formula relationships, correlation coefficients, risk drivers, conditional branching, and rework cycles. |
| decision analysis for the professional: Decision Making in Systems Engineering and Management Gregory S. Parnell, Patrick J. Driscoll, Dale L. Henderson, 2011-03-16 Decision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system. |
| decision analysis for the professional: Decision Analysis for Managers David Charlesworth, 2013-03-13 Everybody has to make decisions—they are unavoidable. Yet we receive little or no education or training on how to make decisions. Business decisions can be dif_ cult: which people to hire, which product lines or facilities to expand and which to sell or shut down, which bid or proposal to accept, which process to implement, how much R&D to invest in, which environmental projects should receive the highest priority, etc. This book gives you all the tools you need to... • clarify and reach alignment on goals and objectives and understand trade-offs in reaching those goals, • develop and examine alternatives, • systematically analyze the effects of risk and uncertainty, and • maximize the chances of achieving your goals and objectives. Success (getting what you want) depends on luck and good decision making. You can’t control your luck, but you can maximize your odds by making the best possible decisions, and this book gets you there. Broadly speaking, this book organizes and presents otherwise formal decision-making tools in an intuitively understandable fashion. The presentation is informal, but the concepts and tools are research-based and formally accepted. |
| decision analysis for the professional: Value of Information in the Earth Sciences Jo Eidsvik, Tapan Mukerji, Debarun Bhattacharjya, 2015-11-19 Gathering the right kind and the right amount of information is crucial for any decision-making process. This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. The authors discuss the value of imperfect versus perfect information, and the value of total versus partial information, where only subsets of the data are acquired. Concepts are illustrated using a suite of quantitative tools from decision analysis, such as decision trees and influence diagrams, as well as models for continuous and discrete dependent spatial variables, including Bayesian networks, Markov random fields, Gaussian processes, and multiple-point geostatistics. Unique in scope, this book is of interest to students, researchers and industry professionals in the Earth and environmental sciences, who use applied statistics and decision analysis techniques, and particularly to those working in petroleum, mining, and environmental geoscience. |
| decision analysis for the professional: Financial Analysis and Decision Making for Healthcare Organizations Louis C. Gapenski, 1996 Financial Analysis & Decision Making for Healthcare Organizations prepares you for the growth of managed care. Dr. Louis Gapenski gives insightful and practical knowledge about financial risk, opportunity costs, asset valuation and financial instruments. Emphasizing the basics for financial decision making, he focuses on five important financial concepts: cash is king, time value of money, risk and return, opportunity costs, and don't put all your eggs in one basket. With applicable real-world examples, financial tables and self examination exercises, Gapenski weaves these concepts throughout each chapter giving you the operational knowledge you need to enhance your financial decision making. |
| decision analysis for the professional: A Handbook on Multi-Attribute Decision-Making Methods Omid Bozorg-Haddad, Babak Zolghadr-Asli, Hugo A. Loáiciga, 2021-04-06 Clear and effective instruction on MADM methods for students, researchers, and practitioners. A Handbook on Multi-Attribute Decision-Making Methods describes multi-attribute decision-making (MADM) methods and provides step-by-step guidelines for applying them. The authors describe the most important MADM methods and provide an assessment of their performance in solving problems across disciplines. After offering an overview of decision-making and its fundamental concepts, this book covers 20 leading MADM methods and contains an appendix on weight assignment methods. Chapters are arranged with optimal learning in mind, so you can easily engage with the content found in each chapter. Dedicated readers may go through the entire book to gain a deep understanding of MADM methods and their theoretical foundation, and others may choose to review only specific chapters. Each standalone chapter contains a brief description of prerequisite materials, methods, and mathematical concepts needed to cover its content, so you will not face any difficulty understanding single chapters. Each chapter: Describes, step-by-step, a specific MADM method, or in some cases a family of methods Contains a thorough literature review for each MADM method, supported with numerous examples of the method's implementation in various fields Provides a detailed yet concise description of each method's theoretical foundation Maps each method's philosophical basis to its corresponding mathematical framework Demonstrates how to implement each MADM method to real-world problems in a variety of disciplines In MADM methods, stakeholders' objectives are expressible through a set of often conflicting criteria, making this family of decision-making approaches relevant to a wide range of situations. A Handbook on Multi-Attribute Decision-Making Methods compiles and explains the most important methodologies in a clear and systematic manner, perfect for students and professionals whose work involves operations research and decision making. |
| decision analysis for the professional: Practical Decision Making Enrique Mu, Milagros Pereyra-Rojas, 2016-08-16 This book offers a simple introduction to the fundamentals and applications of the Analytic Hierarchy Process (AHP) without a pre-requisite for a sophisticated mathematical background. It provides a quick and intuitive understanding of the methodology using spreadsheet examples and explains in a step-by-step fashion how to use Super Decisions, a freely available software developed by the Creative Decisions Foundations. The book is intended to be a resource for decision makers with little or no exposure to the field of Operations Research (OR); however, the book can be used as a very gentle introduction to the AHP methodology and/or as an AHP hands-on supplement for standard OR textbooks. AHP is an intuitive and mathematically simple methodology in the field of multi-criteria decision making. Because of this, most AHP books assume the reader has basic OR mathematical background. However, AHP simplicity suggests that decision makers from all disciplines can take advantage of the methodology without struggling with the mathematics behind it. To fulfill this need, this book delivers a quick and practical understanding of the method that can be useful for corporate executives. |
| decision analysis for the professional: Engineering Decision Making and Risk Management Jeffrey W. Herrmann, 2015-04-06 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. |
| decision analysis for the professional: Location Theory and Decision Analysis Yupo Chan, 2011-08-26 Employing state-of-the art quantitative models and case studies, Location Theory and Decision Analysis provides the methodologies behind the siting of such facilities as transportation terminals, warehouses, housing, landfills, state parks and industrial plants. Through its extensive methodological review, the book serves as a primer for more advanced texts on spatial analysis, including the monograph on Location, Transport and Land-Use by the same author. Given the rapid changes over the last decade, the Second Edition includes new analytic contributions as well as software survey of analytics and spatial information technology. While the First Edition served the professional community well, the Second Edition has substantially expanded its emphasis for classroom use of the volume. Extensive pedagogic materials have been added, going from the fundamental principles to open-ended exercises, including solutions to selected problems. The text is of value to engineering and business programs that offer courses in Decision and Risk Analysis, Muticriteria Decision-Making, and Facility Location and Layout. It should also be of interest to public policy programs that use geographic Information Systems and satellite imagery to support their analyses. |
| decision analysis for the professional: How to Decide Annie Duke, 2020-10-13 Through a blend of compelling exercises, illustrations, and stories, the bestselling author of Thinking in Bets will train you to combat your own biases, address your weaknesses, and help you become a better and more confident decision-maker. What do you do when you're faced with a big decision? If you're like most people, you probably make a pro and con list, spend a lot of time obsessing about decisions that didn't work out, get caught in analysis paralysis, endlessly seek other people's opinions to find just that little bit of extra information that might make you sure, and finally go with your gut. What if there was a better way to make quality decisions so you can think clearly, feel more confident, second-guess yourself less, and ultimately be more decisive and be more productive? Making good decisions doesn't have to be a series of endless guesswork. Rather, it's a teachable skill that anyone can sharpen. In How to Decide, bestselling author Annie Duke and former professional poker player lays out a series of tools anyone can use to make better decisions. You'll learn: • To identify and dismantle hidden biases. • To extract the highest quality feedback from those whose advice you seek. • To more accurately identify the influence of luck in the outcome of your decisions. • When to decide fast, when to decide slow, and when to decide in advance. • To make decisions that more effectively help you to realize your goals and live your values. Through interactive exercises and engaging thought experiments, this book helps you analyze key decisions you've made in the past and troubleshoot those you're making in the future. Whether you're picking investments, evaluating a job offer, or trying to figure out your romantic life, How to Decide is the key to happier outcomes and fewer regrets. |
| decision analysis for the professional: Decision Making Under Uncertainty Charles A. Holloway, 1979 Introduction and basic concepts; Models and probability; Choices and preferences; Preference assessment procedures; Behavioral assumptions and limitations of decision analysis; Risk sharing and incentives; Choices with multiple attributes. |
| decision analysis for the professional: Smart Choices John S. Hammond, Ralph L. Keeney, Howard Raiffa, 2015-08 Where should I live? Is it time to get a new job? Which job candidate should I hire? What business strategy should I pursue? We spend the majority of our lives making decisions, both big and small. Yet, even though our success is largely determined by the choices that we make, very few of us are equipped with useful decision-making skills. Because of this, we often approach our choices tentatively, or even fearfully, and avoid giving them the time and thought required to put our best foot forward. In Smart Choices, John Hammond, Ralph Keeney, and Howard Raiffa--experts with over 100 years of experience resolving complex decision problems--offer a proven, straightforward, and flexible roadmap for making better and more impactful decisions, and offer the tools to achieve your goals in every aspect of your life. Their step-by-step, divide-and conquer approach will teach you how to: * Evaluate your plans * Break your potential decision into its key elements * Identify the key drivers that are most relevant to your goals * Apply systematic thinking * Use the right information to make the smartest choice Smart Choices doesn’t tell you what to decide; it tells you how. As you routinely use the process, you’ll become more confident in your ability to make decisions at work and at home. And, more importantly, by applying its time-tested methods, you’ll make better decisions going forward. Be proactive. Don’t wait until a decision is forced on you--or made for you. Seek out decisions that advance your long-term goals, values, and beliefs. Take charge of your life by making Smart Choices a lifetime habit. |
| decision analysis for the professional: The Great Mental Models, Volume 1 Shane Parrish, Rhiannon Beaubien, 2024-10-15 Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage. |
| decision analysis for the professional: The Decision Model Barbara von Halle, Larry Goldberg, 2009-10-27 In the current fast-paced and constantly changing business environment, it is more important than ever for organizations to be agile, monitor business performance, and meet with increasingly stringent compliance requirements. Written by pioneering consultants and bestselling authors with track records of international success, The Decision Model: A |
| decision analysis for the professional: Decision Quality Carl Spetzler, Hannah Winter, Jennifer Meyer, 2016-02-24 Add value with every decision using a simple yet powerful framework Few things are as valuable in business, and in life, as the ability to make good decisions. Can you imagine how much more rewarding your life and your business would be if every decision you made were the best it could be? Decision Quality empowers you to make the best possible choice and get more of what you truly want from every decision. Dr. Carl Spetzler is a leader in the field of decision science and has worked with organizations across industries to improve their decision-making capabilities. He and his co-authors, all experienced consultants and educators in this field, show you how to frame a problem or opportunity, create a set of attractive alternatives, identify relevant uncertain information, clarify the values that are important in the decision, apply tools of analysis, and develop buy-in among stakeholders. Their straightforward approach is elegantly simple, yet practical and powerful. It can be applied to all types of decisions. Our business and our personal lives are marked by a stream of decisions. Some are small. Some are large. Some are life-altering or strategic. How well we make those decisions truly matters. This book gives you a framework and thinking tools that will help you to improve the odds of getting more of what you value from every choice. You will learn: The six requirements for decision quality, and how to apply them The difference between a good decision and a good outcome Why a decision can only be as good as the best of the available alternatives Methods for making both significant and strategic decisions The mental traps that undermine decision quality and how to avoid them How to deal with uncertainty—a factor in every important choice How to judge the quality of a decision at the time you're making it How organizations have benefited from building quality into their decisions. Many people are satisfied with 'good enough' when making important decisions. This book provides a method that will take you and your co-workers beyond 'good enough' to true Decision Quality. |
| decision analysis for the professional: A Professional's Guide to Decision Science and Problem Solving Frank A. Tillman, Deandra Tillman Cassone, 2012 A Professional's Guide to Decision Science and Problem Solving provides an integrated, start-to-finish framework for more effective problem solving and decision making in corporations. Drawing on vast experience in the field, the authors show how to apply state-of-the-art decision science, statistical modeling, benchmarking, and processing modeling techniques together to create a robust analytical framework for better decision making in any field, especially those that rely on advanced operations management. They integrate both newly-developed and time-tested techniques into a logical, structured approach for assessing corporate issues, developing solutions, and making decisions that drive the successful achievement of corporate objectives. Coverage includes: defining objectives, exploring the environment; scoping problems and evaluating their importance; bringing data mining and statistical analysis to bear; solving problems and measuring the results; evaluating the results and performing sensitivity analysis, and more. The book concludes with three case study chapters that walk through the effective use of its methods, step-by-step. Representing a wide variety of corporate environments, these case studies underscore and demonstrate the method's exceptional adaptability. This book will be valuable in a wide range of industries, notably finance, pharmaceutical, healthcare, economics, and manufacturing. |
| decision analysis for the professional: Harvard Business Review on Decision Making Peter F. Drucker, 2001 This collection of articles guides readers at all levels to understand the fundamental theories and practices of effective decision making in their professional and personal lives. |
| decision analysis for the professional: Multiple Criteria Decision Analysis for Industrial Engineering Gerald William Evans, 2016-12-01 This textbook presents methodologies and applications associated with multiple criteria decision analysis (MCDA), especially for those students with an interest in industrial engineering. With respect to methodology, the book covers (1) problem structuring methods; (2) methods for ranking multi-dimensional deterministic outcomes including multiattribute value theory, the analytic hierarchy process, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and outranking techniques; (3) goal programming,; (4) methods for describing preference structures over single and multi-dimensional probabilistic outcomes (e.g., utility functions); (5) decision trees and influence diagrams; (6) methods for determining input probability distributions for decision trees, influence diagrams, and general simulation models; and (7) the use of simulation modeling for decision analysis. This textbook also offers: · Easy to follow descriptions of how to apply a wide variety of MCDA techniques · Specific examples involving multiple objectives and/or uncertainty/risk of interest to industrial engineers · A section on outranking techniques ; this group of techniques, which is popular in Europe, is very rarely mentioned as a methodology for MCDA in the United States · A chapter on simulation as a useful tool for MCDA, including ranking & selection procedures. Such material is rarely covered in courses in decision analysis · Both material review questions and problems at the end of each chapter . Solutions to the exercises are found in the Solutions Manual which will be provided along with PowerPoint slides for each chapter. The methodologies are demonstrated through the use of applications of interest to industrial engineers, including those involving product mix optimization, supplier selection, distribution center location and transportation planning, resource allocation and scheduling of a medical clinic, staffing of a call center, quality control, project management, production and inventory control,and so on. Specifically, industrial engineering problems are structured as classical problems in multiple criteria decision analysis, and the relevant methodologies are demonstrated. |
DECISION Definition & Meaning - Merriam-Webster
The meaning of DECISION is the act or process of deciding. How to use decision in a sentence.
DECISION | English meaning - Cambridge Dictionary
DECISION definition: 1. a choice that you make about something after thinking about several possibilities: 2. the…. Learn more.
DECISION Definition & Meaning | Dictionary.com
Decision definition: the act or process of deciding; deciding; determination, as of a question or doubt, by making a judgment.. See examples of DECISION used in a sentence.
decision noun - Definition, pictures, pronunciation and usage …
Definition of decision noun in Oxford Advanced American Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Decision - definition of decision by The Free Dictionary
1. the act or process of deciding. 2. the act of making up one's mind: a difficult decision. 3. something that is decided; resolution. 4. a judgment, as one pronounced by a court. 5. the …
What does Decision mean? - Definitions.net
What does Decision mean? This dictionary definitions page includes all the possible meanings, example usage and translations of the word Decision. A choice or judgement. Firmness of …
decision - Wiktionary, the free dictionary
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SUPREME COURT OF THE UNITED STATES
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Decision-making - Wikipedia
In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several …
Decision - Definition, Meaning & Synonyms - Vocabulary.com
To make a decision is to make up your mind about something. To act with decision is to proceed with determination, which might be a natural character trait.
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Planning & Analysis Professional, as defined by the Job Task Analysis Committee is as follows: A newly certified FP&A professional provides insights to the financial decision making process in …
Engineering Ethics and Professional Responsibility
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Using Student Assessment Data to Support Decision-Making …
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A CRITICAL ANALYSIS OF PROFESSIONAL MISCONDUCT
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AN INTRODUCTION TO DECISION ANALYSIS - JSTOR
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Using the Swing Weight Matrix to Weight Multiple Objectives
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Heuristics in Professional Judgement: A Psycho-Social
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Case Article Bayer New Drug Development Decision Making
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Using Student Achievement Data to Support Instructional …
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Practioner's Guide to Ethical Decision Making
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Practioner's Guide to Ethical Decision Making
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Recommendations for Managing Mountain Goats in Montana: …
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Chapter 3 Decision theory - York University
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Critical Thinking and Professional Judgement for Social Work
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Machine Learning for Professional Tennis Match …
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Multi-Criteria Decision Analysis - Wiley Online Library
Multi-criteria decision analysis : methods and software / Alessio Ishizaka, Philippe Nemery. pages cm Includes bibliographical references and index. ISBN 978-1-119-97407-9 (cloth) 1. Multiple …
Ethical decision-making: perspectives - CIPD
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Center for Effective Organizations
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Targeted Professional Development: A Data-Driven …
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Teaching Decision Analysis - JSTOR
teaching decision analysis. Others will have thoughts and experiences to share in these areas, and I do not intend this paper to be definitive. I do, however, hope to ex pand traditional …
