What is Quantitative Risk Analysis?
Quantitative Risk Analysis is a project management technique to numerically evaluate the impact of identified risks on project objectives, cost, schedule and performance. Unlike qualitative risk analysis which classifies risks based on likelihood and severity using subjective scales (e.g. high, medium, low), quantitative analysis uses measurable data and statistical methods to give more precise answers.
The process involves gathering detailed information about risks and then applying mathematical models such as Monte Carlo simulations, decision tree analysis or sensitivity analysis. These methods help project managers estimate the probability of achieving project goals under different risk scenarios. For example, a Monte Carlo simulation can run thousands of possible outcomes to show the probability distribution of project completion dates or costs.
Quantitative risk analysis helps teams answer critical questions like:
- What is the probability of finishing the project on time and within budget?
- How much contingency reserve should I allocate to address uncertainties?
- Which risks, if realized, would have the biggest financial or scheduling impact?
This is especially useful in large, complex or high stakes projects where small mistakes can lead to big delays or cost overruns. By quantifying uncertainty, project managers can make better decisions, gain stakeholder confidence and create realistic contingency plans.