Process: Perform Quantitative Risk Analysis
Process Group: Planning
Knowledge Area: Project Risk Management
Purpose
The Perform Quantitative Risk Analysis process uses numerical techniques to evaluate the overall project risk and quantify the impact of individual risks on project objectives. It supports decision-making by modeling risk interactions and providing probabilistic estimates of outcomes like cost and schedule.
Inputs
- Project Management Plan – Especially the risk management, cost, and schedule baselines.
- Project Documents – Includes the risk register, risk report, cost estimates, schedule forecasts, and resource requirements.
- Enterprise Environmental Factors (EEFs) – Risk databases, simulation tools, and industry benchmarks.
- Organizational Process Assets (OPAs) – Templates, models, and data from similar past projects.
Tools and Techniques
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Expert Judgment – Used to define model assumptions and validate the analysis approach.
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Data Gathering – Interviews or historical data used to establish probability distributions.
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Interpersonal and Team Skills – Facilitation to ensure consistent input from stakeholders and subject matter experts.
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Representations of Uncertainty – Probability distributions (e.g., normal, triangular, beta) for cost and duration inputs.
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Data Analysis
- Monte Carlo simulation – Models combined uncertainty across multiple variables.
- Sensitivity analysis – Identifies which risks have the most significant impact.
- Decision tree analysis – Evaluates expected monetary value (EMV) of decision options.
- Influence diagrams – Visual models of relationships among project variables.
Outputs
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Updated Risk Report – Includes:
- Probabilistic estimates of project duration and cost
- Probability of meeting specific objectives
- Contingency reserve recommendations
- Key drivers of risk exposure
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Project Document Updates – Enhancements to the risk register, assumptions log, and lessons learned register.
Role in the Process Group and Knowledge Area
- Within the Planning Process Group, Perform Quantitative Risk Analysis provides evidence-based insight into how risks affect objectives.
- In Project Risk Management, it supports realistic planning, reserve allocation, and decision support through detailed modeling.
Why It Matters
- Increases Forecast Accuracy – Replaces guesswork with statistically valid projections.
- Prioritizes Risk Drivers – Helps target mitigation efforts to where they will be most effective.
- Supports Strategic Decisions – Equips leadership with objective data to approve funding, contingencies, or go/no-go choices.
- Complements Qualitative Analysis – Deepens understanding of high-priority risks by quantifying their impact.