Quantitative Risk Analysis is the evaluation of the combined effect of identified risks on the desired outcome using numerical methods and modeling techniques. This analysis estimates the potential impact of risk on project objectives—such as cost and schedule—and helps prioritize response strategies based on probability distributions and scenario simulations.
It builds on qualitative risk analysis by providing data-driven insight into overall project exposure.
Key Characteristics
- Numerical Estimation – Uses data to model risk impact in measurable terms
- Probability Distributions – Reflects uncertainty in inputs and outcomes
- Simulation Techniques – Often includes Monte Carlo or decision tree analysis
- Supports Decision-Making – Quantifies risk exposure to inform trade-offs
Example Scenarios
- A Monte Carlo simulation estimates the likelihood of completing a project within budget
- Decision trees are used to compare the cost impact of alternative risk responses
- Schedule modeling shows the probability of meeting critical milestones under uncertainty
Role in Risk Management
- Enables Risk Forecasting – Predicts ranges of outcomes under different risk scenarios
- Supports Cost and Schedule Analysis – Quantifies uncertainty across performance dimensions
- Strengthens Response Planning – Guides selection of strategies based on impact magnitude
- Informs Contingency Reserves – Helps define appropriate buffers for time and budget
See also: Qualitative Risk Analysis, Risk Management Plan, Monte Carlo Simulation, Contingency Reserve, Probability and Impact Matrix.