Decision Analysis Process

This eLearning course introduces decision analysis (DA), the discipline for making informed decisions under uncertainty. The course covers decision modeling, assessing judgments about uncertainties as probability distributions, calculating outcome values, and decision policy. The primary DA calculation tools are decision trees and Monte Carlo simulation. This course equips participants with the skills to make or recommend informed, high-quality decisions in sometimes complex scenarios.

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Target Audience

Geologists, engineers, geophysicists, managers, team leaders, economists, and planners.

You Will Learn

• Follow a 10-step decision-making process in three phases: Framing, Evaluation and Modeling, and Executing. Understand the roles of decision makers, SMEs, and evaluation professionals

• Recognize decision policy components: base value measure, time value, and risk attitude

• Summarize complex problems into structural decision trees or and influence diagrams

• The importance of SME judgments about risks and uncertainties

• Solve simple expected value (EV) calculations with payoff tables, decision trees

• Understand the basic operation of a Monte Carlo simulation. Identify the strengths and weaknesses of each method

• Employ the ten steps in a recommended decision analysis process, and understand the roles of decision makers, SMEs, and evaluation teams

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