This document discusses quantitative risk analysis methods. It describes how to assign probabilities and impacts to risks, calculate risk severity scores, and plot risks on a probability-impact matrix. Monte Carlo simulation and tornado diagrams are presented as techniques for risk modeling and sensitivity analysis. The goal is to prioritize risks for further analysis or risk response planning based on their expected monetary impacts.
In this document
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Overview of qualitative and quantitative risk analysis.
Processes for determining project risk ranking, documenting non-critical risks, and assessing probability and impact.
Prioritizing risks using probability and impact scales for further action or analysis.
Estimation of probability and impact using scales; formulas for calculating severity of risks.
Utilization of probability-impact matrix for classifying risks into categories: high, moderate, low.
Quantitative assessment of risks using numeric scales and risk codes based on probability and impact.
Visual classification of risk based on severity, probability and impact ratings across various risks.
Introduction to expected monetary value analysis and risk management strategies.
Calculation of expected monetary value (EMV) for a potential cost increase scenario.
Managing contingency reserves for risks in a project with a focus on financial implications.
Cost assessment and analysis of various vendors for risk and budget planning.
Techniques used for sensitivity analysis in determining the effects of variable changes.
Utilizing tornado diagrams as a result of sensitivity analysis to analyze project risk factors.
Introduction to Monte Carlo analysis as a tool for managing uncertainty and its relevance.
Detailed explanation of Monte Carlo techniques for project modeling and risk impact assessment.
Discussion on different strategies for managing risks: avoidance, transfer, mitigation, and acceptance.
Identification of strategies for both negative and positive risks in project management.
Definition and management of contingency plans and fallback plans in risk scenarios.
Management reserves, acceptance strategies, and how to reassess risks through audits and variance analysis.
Outline for a project case study focusing on risk management theory and data analysis.