Decision Analysis Process
About the eLearning Course
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.
See example online learning module
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
