Technical training helps us to make decisions on specific types of situations on well studied domains, but these are not all the decisions we technical specialists make or participate in. Many of the most important business and societal decisions have a technical component but they are made on a broader context with conflicting objectives, multiple stake-holders, interrelated uncertain events and very high stakes. Frequently a major challenge on those decision situations is to overcome the complexity of the situation and clear the way for technical solutions to be fully valued and accepted.
Decision Analysis is a discipline that has evolved over the last fifty years to become a most effective and efficient way for making complex decisions. The goal of this course is that participants learn how to analyze complex decision situations and help others and themselves to make sound decisions that maximize the probability of achieving their objectives.
The course will cover a clarity-focused analysis approach (in the tradition of the Stanford school of decision analysis) that includes selecting the best decision situation to analyze, defining and structuring objectives, generating valuable alternatives and strategies, modeling uncertain events using probability trees and relevance diagrams, modeling and evaluating decision situations using influence diagrams, computing the value of acquiring additional information, choosing a strategy based on a clear understanding of the drivers of value, and deciding on how to implement the chosen strategy.
During the course, participants will apply their newly acquired concepts and techniques to real decision situations, acting as decision analysis consultants. Their consulting work will be presented and analyzed throughout the course.
1. Technical decisions and beyond
2. Basic decision analysis concepts
3. Integral Decision Analysis: an overview
4. Choosing the best decision situation to analyze
5. Defining and structuring objectives
6. Generating alternatives and strategies
7. Identifying and modeling uncertain events
8. Modeling decision elements and their interactions
9. Comprehensive evaluation of strategies
10. Choosing a strategy based on clear understanding
11. Deciding on how to implement the chosen strategy
12. Auditing the quality of the decision process
13. Analysis of application projects
14. Decision quality in organizations