Project Risk Management

6.

Perform Quantitative Risk Analysis

6.1.

Purpose and Application

6.1.1.

Numerical Analysis of Risk Effects

6.1.2.

Project Objective Impact Quantification

6.1.3.

Decision-Making Support

6.1.4.

Uncertainty Analysis

6.2.

When to Perform Quantitative Analysis

6.2.1.

Criteria for Application

6.2.1.1.

Project Size and Complexity

6.2.1.2.

Stakeholder Requirements

6.2.1.3.

Risk Significance

6.2.2.

Cost-Benefit Considerations

6.2.2.1.

Analysis Investment

6.2.2.2.

Expected Value of Information

6.2.3.

Organizational Capability

6.2.3.1.

Technical Expertise

6.2.3.2.

Tool Availability

6.3.

Inputs for Quantitative Analysis

6.3.1.

Risk Management Plan

6.3.2.

6.3.3.

Project Management Plan

6.3.4.

Project Documents

6.3.5.

Enterprise Environmental Factors

6.3.6.

Organizational Process Assets

6.4.

The Quantitative Analysis Process

6.4.1.

Risk Selection for Analysis

6.4.1.1.

High-Priority Risk Focus

6.4.1.2.

Quantifiable Risk Identification

6.4.2.

Data Requirements Definition

6.4.2.1.

Probability Distributions

6.4.2.2.

6.4.2.3.

Correlation Factors

6.4.3.

Model Development

6.4.3.1.

Analysis Model Selection

6.4.3.2.

Model Structure Design

6.4.4.

Analysis Execution

6.4.4.1.

Simulation Running

6.4.4.2.

Sensitivity Testing

6.4.5.

Results Interpretation

6.4.5.1.

Statistical Analysis

6.4.5.2.

Practical Implications

6.5.

Data Gathering and Representation

6.5.1.

Expert Interviews

6.5.1.1.

Three-Point Estimates

6.5.1.2.

Range Estimates

6.5.1.3.

Confidence Levels

6.5.2.

Historical Data Analysis

6.5.2.1.

Past Project Performance

6.5.2.2.

Industry Benchmarks

6.5.2.3.

Organizational Databases

6.5.3.

Probability Distributions

6.5.3.1.

Triangular Distribution

6.5.3.1.1.

Optimistic-Most Likely-Pessimistic

6.5.3.1.2.

Distribution Characteristics

6.5.3.2.

Beta Distribution

6.5.3.2.1.

PERT Distribution

6.5.3.2.2.

6.5.3.3.

Normal Distribution

6.5.3.3.1.

Mean and Standard Deviation

6.5.3.3.2.

Application Scenarios

6.5.3.4.

Uniform Distribution

6.5.3.4.1.

Equal Probability Ranges

6.5.3.4.2.

Worst-Case Scenarios

6.5.3.5.

Lognormal Distribution

6.5.3.5.1.

Skewed Distributions

6.5.3.5.2.

Cost and Duration Modeling

6.5.3.6.

Discrete Distributions

6.5.3.6.1.

Specific Outcome Probabilities

6.5.3.6.2.

Event-Based Modeling

6.5.4.

Data Validation

6.5.4.1.

6.5.4.2.

Consistency Checking

6.5.4.3.

Sensitivity Testing

6.6.

Quantitative Risk Analysis Techniques

6.6.1.

Sensitivity Analysis

6.6.1.1.

Single Variable Impact

6.6.1.2.

Tornado Diagrams

6.6.1.2.1.

Risk Driver Identification

6.6.1.2.2.

6.6.1.3.

Spider Diagrams

6.6.1.3.1.

Multi-Variable Analysis

6.6.1.3.2.

Threshold Identification

6.6.2.

Expected Monetary Value (EMV) Analysis

6.6.2.1.

EMV Calculation Methods

6.6.2.2.

Decision Criteria

6.6.2.3.

Risk-Adjusted Values

6.6.3.

Decision Tree Analysis

6.6.3.1.

Decision Node Modeling

6.6.3.2.

Chance Node Modeling

6.6.3.3.

Expected Value Calculation

6.6.3.4.

Decision Path Optimization

6.6.4.

Simulation Techniques

6.6.4.1.

Monte Carlo Simulation

6.6.4.1.1.

Random Sampling Methods

6.6.4.1.2.

Iteration Requirements

6.6.4.1.3.

Convergence Criteria

6.6.4.2.

Latin Hypercube Sampling

6.6.4.2.1.

Stratified Sampling

6.6.4.2.2.

Efficiency Improvements

6.6.4.3.

Simulation Software Tools

6.6.4.3.1.

Commercial Applications

6.6.4.3.2.

Spreadsheet-Based Tools

6.6.5.

Modeling Techniques

6.6.5.1.

Cost Risk Models

6.6.5.1.1.

Bottom-Up Cost Modeling

6.6.5.1.2.

Parametric Cost Models

6.6.5.2.

Schedule Risk Models

6.6.5.2.1.

Critical Path Method Integration

6.6.5.2.2.

Resource Constraint Modeling

6.6.5.3.

Integrated Cost-Schedule Models

6.6.5.3.1.

Resource-Loaded Schedules

6.6.5.3.2.

Correlation Modeling

6.7.

Advanced Quantitative Techniques

6.7.1.

Real Options Analysis

6.7.1.1.

Option Valuation Methods

6.7.1.2.

Flexibility Value Assessment

6.7.2.

Value at Risk (VaR)

6.7.2.1.

Risk Exposure Quantification

6.7.2.2.

Confidence Level Selection

6.7.3.

Conditional Value at Risk

6.7.3.1.

Tail Risk Assessment

6.7.3.2.

Expected Shortfall

6.8.

Correlation and Dependency Modeling

6.8.1.

Risk Interdependencies

6.8.1.1.

Correlation Coefficients

6.8.1.2.

Dependency Structures

6.8.2.

Common Cause Variations

6.8.2.1.

Shared Risk Factors

6.8.2.2.

Systematic Risks

6.9.

Interpreting Quantitative Results

6.9.1.

Statistical Measures

6.9.1.1.

Mean and Standard Deviation

6.9.1.2.

Percentile Analysis

6.9.1.3.

Confidence Intervals

6.9.2.

Probabilistic Analysis Results

6.9.2.1.

Probability of Success

6.9.2.2.

Risk Exposure Calculations

6.9.2.3.

Contingency Requirements

6.9.3.

Risk Driver Analysis

6.9.3.1.

Critical Risk Identification

6.9.3.2.

Risk Contribution Assessment

6.9.4.

Scenario Analysis

6.9.4.1.

Best Case Scenarios

6.9.4.2.

Worst Case Scenarios

6.9.4.3.

Most Likely Scenarios

6.9.5.

Communicating Results

6.9.5.1.

Executive Summaries

6.9.5.2.

Technical Reports

6.9.5.3.

Visual Presentations

6.10.

Model Validation and Verification

6.10.1.

Model Accuracy Testing

6.10.2.

Assumption Validation

6.10.3.

Sensitivity to Input Changes

6.10.4.

Historical Validation

6.11.

Outputs of Quantitative Analysis

6.11.1.

Risk Register Updates

6.11.1.1.

Quantified Risk Assessments

6.11.1.2.

Prioritized Risk Lists

6.11.1.3.

Risk Response Cost-Benefit Analysis

6.11.2.

Risk Report Updates

6.11.2.1.

Quantitative Risk Analysis Results

6.11.2.2.

Probabilistic Analysis Summary

6.11.3.

Project Documents Updates

6.11.3.1.

Cost Baseline Updates

6.11.3.2.

Schedule Baseline Updates

6.11.3.3.

Risk-Adjusted Estimates

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