Uncertainty Analysis Alternatives: Decision Tree and Multicriteria Analysis

PMBOK v8 Definition

Uncertainty Analysis Alternatives encompass two key techniques for evaluating options under uncertainty: Multicriteria Decision Analysis and Decision Tree Analysis. Multicriteria Decision Analysis uses a decision matrix to provide a systematic analytical approach for establishing criteria, such as risk levels, uncertainty, and valuation, to evaluate and rank many ideas. Decision Tree Analysis is a diagramming and calculation technique for evaluating the implications of a chain of multiple options in the presence of uncertainty, used to support selection of the best of several alternative courses of action. (Process Group: Planning; Knowledge Area: Risk Management)

Why It Matters for the Exam

This concept appears frequently in PMI exam questions testing your ability to select the correct analytical technique for risk-based decision-making. You will encounter it in situational questions where the project manager must choose between multiple alternatives under uncertainty, and in direct knowledge questions distinguishing between Multicriteria Decision Analysis and Decision Tree Analysis.

Key Points to Remember (for the exam)

• Main Purpose: Both techniques support decision-making when uncertainty exists, but they serve different scenarios
• Multicriteria Decision Analysis: Uses a decision matrix with weighted criteria (risk levels, uncertainty, valuation) to evaluate and rank many ideas; tools include prioritization matrix and Analytic Hierarchy Process (AHP)
• Decision Tree Analysis: Uses branches representing different decisions or events, each with associated costs and related individual project risks (threats and opportunities); evaluated by calculating Expected Monetary Value (EMV) for each branch
• Key Distinction: Multicriteria Decision Analysis ranks many ideas using weighted criteria; Decision Tree Analysis selects the best path through sequential decisions using EMV calculations
• Decision Tree Components: Branches show alternative paths; end points represent outcomes (negative or positive); each branch has costs and associated risks
• Common Confusion: Confusing Multicriteria Decision Analysis with Decision Tree Analysis—remember that multicriteria uses a matrix with weighted criteria, while decision trees use a diagram with EMV calculations
• Exam Favorite: Decision Tree Analysis is frequently tested with EMV calculations where you must calculate the value of each branch and select the optimal path

Typical PMI Exam Example

A project manager is evaluating two software development approaches for a new product. Approach A has a 60% chance of success with $200,000 profit and 40% chance of failure with $50,000 loss. Approach B has an 80% chance of success with $150,000 profit and 20% chance of failure with $30,000 loss. Using Decision Tree Analysis, calculate the EMV for each approach: Approach A = (0.6 × $200,000) + (0.4 × -$50,000) = $100,000; Approach B = (0.8 × $150,000) + (0.2 × -$30,000) = $114,000. Select Approach B (higher EMV).

PMI Exam Traps

• Trap: Confusing Multicriteria Decision Analysis with Decision Tree Analysis

  • Reality: Multicriteria uses a decision matrix with weighted criteria to rank many ideas; Decision Tree uses a diagram with EMV calculations for sequential decisions

• Trap: Thinking Decision Tree Analysis only considers threats (negative risks)

  • Reality: Decision trees include both threats and opportunities (positive and negative outcomes)

• Trap: Assuming Multicriteria Decision Analysis is subjective or lacks structure

  • Reality: It is a systematic analytical approach where criteria are prioritized and weighted before being applied to all alternatives, producing mathematical scores

• Trap: Confusing Decision Tree Analysis with Influence Diagrams

  • Reality: Decision trees show sequential decisions with branches and EMV calculations; Influence diagrams show causal relationships and are evaluated using Monte Carlo simulation

Important PMI Connections

Quick Review Questions

1. What technique uses a decision matrix with weighted criteria to evaluate and rank many ideas under uncertainty?

2. How is a Decision Tree evaluated to determine the optimal path?

3. What types of risks can be associated with branches in a Decision Tree analysis?

4. Which technique would you use to select the best course of action when facing sequential decisions with probabilistic outcomes?

5. What is the difference between Multicriteria Decision Analysis and Decision Tree Analysis in terms of their analytical approach?

PMBOK v8 Reference

Section 5.2.2.3 - "Multicriteria Decision Analysis" (also referenced in Risk Management context)

Section 5.2.2.4 - "Decision Tree Analysis" (also referenced in Risk Management context)