Introduction to Decision Analysis

Course 1255

  • Duration: 4 days
  • Labs: Yes
  • Language: English
  • Level: Foundation

This hands-on Introduction to Decision Analysis gives you the tools required to make better, more informed and justifiable decisions. The focus is on thinking creatively about issues and then applying structured, formal analysis to spur action. A range of tools are considered, providing a comprehensive toolkit for those willing to enhanced the effectiveness of their organisational, or personal, decision-making.

The focus of this course is on lightweight, rapid, "agile" modelling---cycling rapidly between problem, definition, analysis, conclusions and actions. Emphasis is placed on structuring of assumptions, as opposed to mathematical modelling.

The course does not provide a "deep dive" into the techniques presented. It is intended to give you an overview of the field and act as a foundation for deeper study of the techniques that are most appropriate to your current and/or future decision-making needs.

Participants should be familiar with Microsoft Excel and be able to understand basic mathematical concepts (high-school level).

Anyone who is involved in decision-making! Including those who are looking to make important personal decisions, or those who support decision-makers.

Executives (decision-makers), project managers, strategy analysts, business analysts are data scientists are all formal job roles that would obviously benefit from the course, but everyone is involved in making decisions at some level. Participants should be familiar with Microsoft Excel.

Introduction to Decision Analysis Delivery Methods

  • After-course instructor coaching benefit
  • After-course computing sandbox included
  • Learning Tree end-of-course exam included

Introduction to Decision Analysis Course Benefits

Structure your decision analysis projectsUnderstand and interpret uncertaintyRecognise and mitigate psychological biasesUncover cause and effect relationshipsEvaluate alternatives using multi-criteria decision analysisPeer into the future using forecastingApply game theory to develop strategy in the face of competitionExplore complex issues using network analysis and simulationLeverage the benefits, and avoid the pitfalls, of teams in the decision-making process

Introduction to Decision Analysis Course Outline

  • What makes a good decision?
  • History of decision analysis
  • Problem solving
  • Creative thinking
  • Data science vs decision analysis
  • Bulletproof Problem Solving
  • OODA loop
  • Conducting research
  • Definition and categorization
  • Thinking probabilistically
  • Expected value
  • Visualising uncertainty
  • Utility curves
  • Psychological biases
  • Correlation
  • Regression
  • Monte Carlo methods
  • Forced ranking
  • Decision matrices
  • Multi-criteria decision analysis Decision trees
  • Time series
  • Expert judgement
  • Prediction markets
  • Scenario planning
  • Stakeholder analysis
  • Game theory
  • Confrontation analysis
  • Feedback loops
  • Influence diagrams
  • System dynamics
  • Strategy mapping
  • Wisdom of crowds
  • Delphi method
  • Voting

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Course FAQs

Decision analysis is a formal, structured, systematic and visual approach to evaluating problems that leads to decisions and action. It utilises a range of methods, models and tools to aid in the capture, analysis and synthesis of information---both qualitative and quantitative---that is germane to the issue at hand. You can utilise decision analysis at different scales---from personal decision-making to long-range international policy planning. Tools commonly used by decision analysts include decision trees, game theory, statistical modelling and simulation.

Decision analysis removes the need for key business decisions to be made on "gut feel". Formalizing the decision-making process foster collaboration, and allows decisions to be reviewed and audited prior to irreversible decisions being taken. The ability to show a clear decision path can be invaluable in highly regulated industries. Companies such as Chevron have made decision analysis a core competence.

Participants should be familiar with Microsoft Excel and be able to understand basic mathematical concepts (high-school level).

Yes. There are various opportunities to build model and analyses issues throughout the period of the training.

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