Perform Quantitative Risk Analysis

Where qualitative analysis ranks risks relative to each other, quantitative analysis puts actual numbers behind them — probabilities, dollar values, schedule impacts — so decisions can be made on calculated outcomes rather than relative judgment alone. It starts with analyzing risk data and process performance information against the metrics established earlier, plus forecasting and trend analysis using both new and historical information.

Sensitivity analysis is the core technique cluster here, and PMI names several specific tools: Monte Carlo simulation (running a model many times with varying inputs to see a range of possible outcomes), decision trees (mapping out choices and their probable outcomes to compare expected value across paths), critical path analysis (understanding which schedule risks actually threaten the project's end date), and Expected Monetary Value, or EMV (probability multiplied by impact, summed across possible outcomes, to get one comparable number per risk). The task closes with risk weighting and calculating overall risk priority from these quantitative results.

Study focus: EMV is a near-guaranteed calculation question. EMV = Probability × Impact for each possible outcome, summed together — know it well enough to compute it directly from a simple scenario, not just recognize the term.