Cover image for Risk and decision analysis in projects
Risk and decision analysis in projects
Title:
Risk and decision analysis in projects
Author:
Schuyler, John R., 1950-
ISBN:
9781628700541
Personal Author:
Edition:
2nd ed.
Publication Information:
Newtown Square, Pa. : Project Management Institute, c2001.
Physical Description:
1 online resource (xiii, 259 p.) : ill.
Contents:
Risk and Decision Analysis Decision Problems Credible Analysis Risk and Uncertainty Frequency and Probability Distributions Expected Value Summary: Expected Value, the Best Estimator Moment Methods Popular Equations Correlation Decision Analysis Process Ten Steps toward Better Decisions Who Does All This Work? Decision Policy Intuition Is a Poor Method Decision Maker's Preferences Attitude toward Different Objectives Attitude toward Time Value Attitude toward Risk Decision Policy Summary Crane Size Decision Utility and Multi-Criteria Decisions Exceptions to Expected Monetary Value Decision Policy Conservative Risk Attitude Utility Function for Risk Policy Multi-Criteria Decisions Three Pillars of Decision Analysis Decision Policy Summary Decision Trees Decision Trees Wastewater Plant Example Tree Software Decision Tree Summary Value of Information Revisiting the Wastewater Plant Problem Value of Information Plant Information Alternative Value of Information Summary Bayesian Analysis Killing the Project in Time Early Warnings Gateways Point-Forward Analysis Options Add Value Feel Good about Your Decision Monte Carlo Simulation Approximating Expected Value Wastewater Plant Revisited Monte Carlo Technique Wastewater Plant Simulation Simulation in Practice Comparing Simulation to Trees Project Risk Management -- By the Numbers The Business Perspective Model Scope PMBOK Guide Sections Pre-Project Risk Management During the Project Keep Your Perspective Quick-and-Dirty Decisions Common Simple Situation Risk Management Plan Sensitivity Analysis Evaluating Alternatives Mitigating and Avoiding Risks Portfolio Risks Commodity Prices Interest Rate and Exchange Rate Environmental Hazards Operational Risks Analysis Risks (Reducing Evaluation Error) Comparison with the PMBOK Guide -- 2000 Edition Asset Value Perspective Continuous Risk Events Risk Prioritization Needs Quantification Modeling and Inputs -- Modeling Techniques Forecasts from Models Deterministic Project Models Deterministic Cashflow Models Modeling Process Modeling Tools Sensitivity Analysis Dynamic Simulation Models Summary -- Toward Credible Evaluations Probability Distribution Types Probability Distributions Discrete Distributions Continuous Distributions Which Distribution Is Best? Judgments and Biases Three Roles Judgments Biases Improving Evaluations Relating Risks Correlation Sources of Correlation Ways to Represent Correlation Human Factors Stochastic Variance Base Case versus Stochastic Model Variance Analysis New Venture Analysis Exploiting the Best of Critical Chain and Monte Carlo Simulation Critical Chain Decision Analysis with Monte Carlo Simulation Comparing Approaches Combining Methods Optimizing Project Plan Decisions It's an Optimization Problem Example Project Model Optimizing Activity Starts Incentives Optimization Experience Simplifying Project Decisions Probability Rules Venn Diagrams and Boolean Algebra Key Probability Theorems Thinking Logically Expert Systems in Project Management Smart Computers Expert Systems Neural Networks Fuzzy Logic Summary of Methods Some Additional Methods Deterministic or Stochastic? Decision Analysis Software Spreadsheets Monte Carlo Simulation Decision Tree Analysis Project Risk Management
Abstract:
Annotation Schuyler has over 25 years of experience in economic evaluation, training, and management. Here he presents a text on decision analysis (DA), the discipline which aids decision makers in making sound choices under conditions of uncertainty. Coverage includes an overview of the concept of decision analysis; how DA applies to project risk management; a general problem-solving process; details about project modeling; the use of probability distributions for uncertain inputs; some emerging techniques including critical chain project management, optimization, and expert systems; and a brief tutorial about probability rules. The text is based on articles contributed by the author to the magazine, PM Network, from 1992 through 2000. Written for project managers. Annotation c. Book News, Inc., Portland, OR (booknews.com).

Annotation Some of Schuyler's tried-and-true tips include: - The single-point estimate is almost always wrong, so that it is always better to express judgments as ranges. A probability distribution completely expresses someone's judgment about the likelihood of values within the range.- We often need a single-value cost or other assessment, and the expected value (mean) of the distribution is the only unbiased predictor. Expected value is the probability-weighted average, and this statistical idea is the cornerstone of decision analysis.- Some decisions are easy, perhaps aided by quick decision tree calculations on the back of an envelope. Decision dilemmas typically involve risky outcomes, many factors, and the best alternatives having comparable value. We only need analysis sufficient to confidently identify the best alternative. As soon as you know what to do, stop the analysis!- Be alert to ways to beneficially change project risks. We can often eliminate, avoid, transfer, or mitigate threats in some way. Get to know the people who make their living helping managers sidestep risk. They include insurance agents, partners, turnkey contractors, accountants, trainers, and safety personnel.
Holds: Copies: