{"product_id":"risk-and-decision-analysis-in-john-r-schuyler-9781719014236","title":"Risk and Decision Analysis in Projects 3.1 Edition","description":"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: \u003cb\u003eDecision trees\u003c\/b\u003e and \u003cb\u003eMonte Carlo simulation\u003c\/b\u003e for calculating outcome distributions and expected values - Probability concepts, including Bayes' rule for \u003cb\u003evalue of information analysis\u003c\/b\u003e - Popular probability \u003cb\u003edistribution types\u003c\/b\u003e and when they apply - \u003cb\u003eEliciting expert judgments\u003c\/b\u003e, with attention to potential cognitive and motivational biases - Recognizing the \u003cb\u003ethree pillars\u003c\/b\u003e project in terms of project value - A 10-step decision analysis process - Project modeling concepts and techniques, with special attention to \u003cb\u003erisk drivers\u003c\/b\u003e and other \u003cb\u003ecorrelations\u003c\/b\u003e - Deterministic and stochastic \u003cb\u003esensitivity analysis\u003c\/b\u003e - \u003cb\u003eDecision policy\u003c\/b\u003e that distinguishes objectives, time value, and risk attitude - @RISK(R) with Microsoft(R) Project for project simulations under uncertainty - Logical, consistent \u003cb\u003erisk policy\u003c\/b\u003e expressed as a utility function - \u003ci\u003eMerge bias\u003c\/i\u003e when task chains converge at a merge point - \u003ci\u003eTail estimate bias\u003c\/i\u003e when estimating highly uncertain quantities - \u003ci\u003eOptimizer's curse\u003c\/i\u003e, a portfolio forecasting bias - \u003ci\u003eWinner's curse\u003c\/i\u003e, a bias characteristic of auctions - Using the best of \u003cb\u003ecritical chain\u003c\/b\u003e and Monte Carlo simulation - \u003ci\u003eStochastic variance\u003c\/i\u003e between a deterministic and a stochastic model - \u003cb\u003eModeling\u003c\/b\u003e risk and uncertainty using probabilities, probability distributions, explicit formula relationships, correlation coefficients, risk drivers, conditional bra\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e John R. Schuyler\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 171901423X\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9781719014236\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Createspace Independent Publishing Platform\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 08\/21\/2018\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 520\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 2.63lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 11.02h x 8.50w x 1.05d","brand":"John R. Schuyler","offers":[{"title":"Paperback","offer_id":43989456322815,"sku":"9781719014236","price":39.95,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_a5f3c136-f8fd-4094-b358-df195445bfa0.jpg?v=1683299606","url":"https:\/\/www.whiterainbookhouse.com\/products\/risk-and-decision-analysis-in-john-r-schuyler-9781719014236","provider":"WR Book House","version":"1.0","type":"link"}