"A good science and engineering decision is a good business decision."


 

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Important Concept Summaries
Decision Dilemmas white paper

Decisions with Risk

 What Every Executive Should Know
about Decision Analysis

working title of a planned, short book by John Schuyler
(you may have been transferred to this page from www.decisionswithrisk.com)

Decision-makers are increasingly presented with probabilistic analyses supporting a recommended investment. The purpose of this book is to help executives understand the principles and methods of decision analysis. The decision-maker owns the decision and should be engaged in the analysis process.

People in our decision analysis courses often say, "My boss should be hearing this."¾particularly when we're discussing decision policy. We will be providing copies of this book (or equivalent online access) for course participants to take back to their bosses.

To get started, ten "Important Concept Summaries" (ICs) have been pulled from course materials. Each is about three pages. They are listed with links at the page bottom.

Tentative Chapters

  • What is decision analysis?  whitepaper: "Resolving Decision Dilemmas"
  • The decision analysis process and the role of the decision-maker
  • Framing and structuring the problem
  • Decision policy elements, including risk policy
  • Interpreting charts and numeric results of a decision analysis
    (Probabilities and probability distributions)
  • Additional probability concepts
  • Decision tree analysis
  • Monte Carlo simulation
  • Delegating responsibility: the executive's role in ensuring decision quality
    ("Drilling down into the analysis"-some probing questions to ask)

                      Appendices
  • Decision analysis provides more accurate estimates and forecasts
  • Business modeling of projects, portfolios and the enterprise
  • Health, Safety and the Environment (HSE)
    (corporate social responsibility)
  • Determining risk tolerance
  • Sensitivity analysis
  • Optimizing decision variables
  • Judgments and biases
  • Improving decisions: Value of information, flexibility and control
  • Portfolio concepts and enterprise risk management
  • Project modeling and project risk management

 

Important Concept Summaries

IC 1 PRESENT VALUE
IC 2 EXPECTED VALUE
IC 3 PROBABILITY DISTRIBUTIONS
IC 4 BUSINESS MODELING
IC 5 SIMULATION
IC 6 BASIC PROBABILITY CONCEPTS
IC 7 DECISION TREES
IC 8 BAYES' RULE
IC 9 VALUE OF INFORMATION AND CONTROL
IC 10 RISK POLICY

 

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