10 4 Perform Quantitative Risk Analysis
10.4 Perform Quantitative Risk Analysis Explained
Perform Quantitative Risk Analysis is a critical process in project management that involves numerically assessing the impact of identified risks on overall project objectives. This process helps in prioritizing risks, making informed decisions, and allocating resources effectively. Here, we will delve into four key concepts of Perform Quantitative Risk Analysis: Probability and Impact Assessment, Expected Monetary Value (EMV), Decision Tree Analysis, and Sensitivity Analysis.
1. Probability and Impact Assessment
Probability and Impact Assessment involves determining the likelihood of each identified risk occurring and the potential impact it would have on project objectives. This assessment helps in understanding the overall risk exposure and prioritizing risks based on their potential impact.
Example: For a construction project, the probability of encountering a labor strike might be assessed at 30%, and the impact on the project timeline could be a delay of two weeks. This assessment helps in understanding the potential risk exposure and planning mitigation strategies accordingly.
2. Expected Monetary Value (EMV)
Expected Monetary Value (EMV) is a statistical technique used to quantify the expected financial impact of risks. EMV is calculated by multiplying the probability of each risk by its financial impact and summing the results. This helps in understanding the overall financial exposure of the project.
Example: If a risk has a 40% probability of occurring and a financial impact of $50,000, its EMV would be $20,000 (0.40 * $50,000). By calculating the EMV for all identified risks, project managers can understand the total financial exposure and allocate contingency funds accordingly.
3. Decision Tree Analysis
Decision Tree Analysis is a graphical method used to evaluate the potential outcomes of different decisions and their associated risks. It helps in selecting the best course of action by considering the probabilities and impacts of each outcome.
Example: In a software development project, a decision tree might be used to evaluate whether to develop a new feature in-house or outsource it. The tree would show the potential costs, benefits, and risks associated with each option, helping the project team make an informed decision.
4. Sensitivity Analysis
Sensitivity Analysis involves assessing how changes in key variables affect the overall outcome of the project. This analysis helps in identifying which risks have the most significant impact on project objectives and prioritizing them for further action.
Example: For a marketing campaign, sensitivity analysis might involve changing the budget allocation and observing the impact on campaign success metrics such as reach and conversion rates. This helps in understanding which budget changes have the most significant impact and optimizing the campaign accordingly.