Other Sources Uncertainty: Simulation and Monte Carlo Analysis

PMBOK v8 Definition

Simulation models the combined effects of individual project risks and other sources of uncertainty to evaluate their potential impact on achieving project objectives. The most common simulation technique is Monte Carlo analysis, in which risks and other sources of uncertainty are used to calculate possible schedule outcomes for the total project. Simulation involves calculating multiple work package durations with different sets of activity assumptions, constraints, risks, issues, and other variables.

Why It Matters for the Exam

The PMI exam frequently tests your understanding of how simulation handles multiple simultaneous uncertainties—not just individual risks. Questions appear in the Risk and Schedule domains, often asking you to identify which technique models combined effects of risks AND uncertainty sources (ambiguity, variability). Expect scenario-based questions where you must select Monte Carlo simulation over deterministic or single-point estimation methods.

Key Points to Remember (for the exam)

• Core Purpose: Models combined effects of individual project risks AND other sources of uncertainty (not just risks alone)
• Most Common Technique: Monte Carlo analysis—calculates possible schedule outcomes for the total project
• Inputs Include: Activity assumptions, constraints, risks, issues, and sources of ambiguity
• Outputs Produced: Probability distributions (S-curves), tornado diagrams showing correlation coefficients, and influence diagrams
• Key Distinction: Simulation ≠ sensitivity analysis—simulation models combined effects; sensitivity analysis (tornado diagram) shows which single elements have greatest influence
• Application Domain: Primarily used for schedule and cost risk analysis, not quality or scope
• Exam Focus: Recognize that simulation addresses both aleatory uncertainty (variability) and epistemic uncertainty (ambiguity)

Typical PMI Exam Example

A project manager is developing the project schedule and identifies that several activities have high variability in duration due to both identified risks and inherent process uncertainty. The sponsor asks for a realistic range of possible completion dates. Which technique should the project manager use?

Answer: Monte Carlo simulation, because it models the combined effects of individual project risks and other sources of uncertainty to calculate possible schedule outcomes.

PMI Exam Traps

• Trap: Confusing simulation with sensitivity analysis (tornado diagram) Reality: Simulation models combined effects of multiple uncertainties; tornado diagrams show the individual influence of each element on outcomes

• Trap: Thinking simulation only addresses identified risks Reality: Simulation includes other sources of uncertainty such as variability, ambiguity, and unknown unknowns

• Trap: Assuming Monte Carlo is only for cost analysis Reality: Monte Carlo is commonly used for schedule outcomes, calculating possible durations with different sets of activity assumptions

• Trap: Confusing simulation with what-if scenario analysis Reality: Simulation runs thousands of iterations with random variable inputs; what-if analysis tests specific predetermined scenarios

Important PMI Connections

Quick Review Questions

1. What is the most common simulation technique used in project management, and what does it calculate?

2. A project has 15 identified risks and 3 activities with high duration variability. Which technique models the combined effect of ALL these uncertainties on the project completion date?

3. How does a tornado diagram differ from the simulation output that creates it?

4. True or False: Simulation only models individual project risks, not sources of ambiguity or variability.

5. In a Monte Carlo simulation, what types of inputs are varied across different iterations?

PMBOK v8 Reference

Section 5 – Tools and Techniques (pages 196-197)