Overview

ADVANCED DECISION ANALYSIS (ADA) with PROJECT AND PORTFOLIO MODELING

About the Course

 A well-designed project and portfolio model that is built upon a defined decision policy, solid professional judgements, and a good decision process is essential for producing high-quality forecasts and evaluations. Participants in this workshop develop their modeling skills. We base our project and risk assessment models on the well-known Microsoft Excel spreadsheet. Decision tree and Monte Carlo capabilities are offered via add-on software. The focus of the course is on evaluation concepts and approaches rather than specific software applications.

Target Audience

 engineers, analysts, managers, planners, and economists involved in evaluation. Professionals working on project evaluation, portfolio development, and other forecasting and assessment models are the target audience for this course. Decision analysis experience is expected. Please visit http://www.decisionapplications.com/ada-pre-read/ to examine the course prerequisites and to complete a brief self-assessment quiz prior to registering. 'ada' (without quotes) can be used as your login password.

Course Objectives

 Participants will pick up skills in:

•  Create, test, and evaluate decision models while gaining important insights For risk management, use the exponential utility function.
• Create models for optimizing investment portfolios that take limitations, specifications, and typical project linkages into account.
• Utilize decision tree software to analyze the value of incomplete information.
• Applying optimization to Monte Carlo simulation software
• Create top-notch Excel models for your projects and portfolios.

 Course Outlines

•  Application of the Decision Analysis (DA) approach for modeling, influence diagrams, sensitivity analysis, effective modeling practices, and an overview of genuine options
• Monte Carlo Simulation: multi-pay prospect risking (similar to play analysis), computing probabilities and distributions through simulation, modeling and optimizing investment portfolios, valuing extra control and flexibility, halting rules, and methods to simulate correlation
• Review of informational value, sensitivity analysis, and utility-based problem-solving for risk aversion
• Portfolio optimization to maximize value is the chosen decision policy; Optimum working interests, efficient frontiers, multi-criteria decisions, expected utility and certain equivalent, risk policy as a utility function, insurance, and hedging
• mplementation: obtaining preferences for trade-offs between objectives, time value, and risk attitude from a decision maker or organization; Agendas and styles for decision analysis presentations; unique subjects drawn from the instructor's own study and expertise