Quantitative Risk Analysis: Measure the risk impact using specified project management techniques that align quantitative risk factors to the qualitative risk analysis. You can add monetary or time elements to the risks from the qualitative risk analysis.
A decision tree is a diagram that models a series of decisions and their possible outcomes, including risks and rewards. It is used when a decision point introduces uncertainty (risk). The EMV is calculated at each potential outcome, and the optimal path is the one with the highest positive EMV.
Application: Used to make choices under uncertainty, such as "Should we prototype the product (high cost, low risk) or go straight to full production (low cost, high risk)?"
Monte Carlo analysis is a computer-based simulation technique that models the possible outcomes of a project by running thousands of iterations.
Input: The technique requires probability distributions (optimistic, pessimistic, and most likely values) for cost and/or time for all critical path activities.
Simulation: It randomly selects values for each activity based on its distribution and calculates the project's total cost and/or duration for that iteration.
Output: The result is a probability distribution graph showing the likelihood of completing the project by a certain date or within a certain budget.
Quantitative Alignment: If your qualitative analysis identified "Complexity of Integration" as a high-impact risk, Monte Carlo simulation can show the 75% confidence level that the project will be completed within 18 months and $2.5 million.
Application: Provides the most comprehensive view of overall project risk (the "P-Value"), helping to set realistic cost and schedule targets.
Sensitivity analysis is used to determine which specific project risks or uncertainties have the greatest potential impact on the project outcome (e.g., net present value, cost, or schedule).
Process: It involves changing only one input variable at a time (e.g., the cost of a specific resource or the duration of an activity) while holding all others constant.
Output: The results are usually presented in a Tornado Diagram, which visually ranks risks based on the magnitude of their effect.
Quantitative Alignment: If a specific material cost fluctuation was a key qualitative risk, the Tornado Diagram quantifies that a 10% increase in that cost could lead to a 15% increase in total project cost, making it the most impactful variable.
Application: Prioritizes the most critical risks, enabling the project manager to focus mitigation efforts where they will have the greatest effect.
To measure risk impact quantitatively, you can use several project management techniques that align with the risks identified during qualitative analysis. These techniques assign numerical values (monetary or time) to the probability and impact of risks, allowing for calculation of the project's overall exposure.
Here are the key techniques used for Quantitative Risk Analysis:
The EMV technique calculates the average outcome of a risk event by multiplying its Probability (P) of occurrence by its Impact (I) in monetary terms. This provides a numerical value for the risk exposure, which can then be added to the project budget as a contingency reserve.