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Simulation

A quantitative method that imitates project outcomes under multiple uncertainties to assess how those combined variations could influence objectives.

Key Points

  • Runs many iterations using random inputs to reflect uncertainty and produce a range of possible results.
  • Often applied to cost and schedule to estimate the likelihood of meeting targets and required contingency.
  • Needs input ranges, probability distributions, and any correlations among variables to be credible.
  • Outputs include probabilities (e.g., P50, P80), outcome ranges, and sensitivity to key drivers.

Example

A project team assigns three-point estimates and distributions to activity durations and costs, then runs a Monte Carlo simulation with 10,000 iterations. The results show a 72% chance of finishing by November 30, a P80 cost of $1.95M, and a tornado chart revealing two design tasks as the main drivers of schedule risk.

PMP Example Question

A project manager wants to know the probability of finishing within 30 weeks and under $2M, given uncertain activity durations and material prices. Which technique should be used?

  1. Sensitivity analysis
  2. Simulation (Monte Carlo)
  3. Three-point estimating
  4. Trend analysis

Correct Answer: B — Simulation

Explanation: Simulation models the combined effect of multiple uncertainties to produce probability-based outcomes for time and cost objectives.

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