Day 1: Fundamentals of Project Risk Management & PRA Introduction

• Introduction to Project Risk Management:
  • Definitions: Risk, Uncertainty, Threat, Opportunity.
  • PMI Risk Management Process: Planning, Identification, Analysis (Qualitative & Quantitative), Response, Monitoring & Control.
  • Why quantitative risk analysis is critical for complex projects.
• Introduction to Primavera Risk Analysis (PRA):
  • Overview of PRA's capabilities and place in the project management toolkit.
  • PRA Software Interface: Layout, navigation, key windows.
  • Project Import/Integration:
    • Importing schedules from Primavera P6 (XER files), Microsoft Project (XML/MPP), and other formats.
    • Mapping activity fields and resources.
    • Validating the imported schedule for risk analysis.
• Setting up a Project in PRA:
  • Calendars, resources, WBS elements.
  • Defining Project Settings for analysis.
• Workshop: Navigating the PRA interface and importing a sample project schedule from P6/MS Project, performing initial schedule validation

Day 2: Qualitative Risk Analysis & Schedule Risk Setup in PRA

• Qualitative Risk Analysis in PRA:
  • Building and managing a Risk Register in PRA.
  • Risk Identification Techniques (Brainstorming, Interviews, Checklists).
  • Probability & Impact Assessment (P-I Matrix) in PRA.
  • Defining Risk Categories and Owners
• Modeling Schedule Uncertainty in PRA:
  • Understanding activity duration uncertainty.
  • Selecting appropriate Probability Distributions for durations: Triangular, Beta (PERT), Uniform, Normal, etc.
  • Applying distributions to activities (3-point estimates).
  • Understanding statistical concepts relevant to PRA (Mean, Standard Deviation).
• Linking Risks to Schedule Activities:
  • Assigning discrete risk events from the risk register to specific activities or groups of activities.
  • Defining the impact of risk events on duration, cost, or logic.
  • Creating Conditional Branching (Logical Risks).
• Practical Exercise: Populating a risk register in PRA, assigning P-I ratings, and applying 3-point duration estimates to selected activities in the imported schedule.

Day 3: Performing Quantitative Schedule Risk Analysis (QSRA) with PRA

• Monte Carlo Simulation Fundamentals:
  • How Monte Carlo simulation works in PRA.
  • Number of iterations, random seeds.
  • Confidence levels and P-values (P10, P50, P90).
• Running a Quantitative Schedule Risk Analysis (QSRA):
  • Setting up the analysis parameters in PRA.
  • Executing the simulation.
• Interpreting QSRA Results:
  • S-Curves (Cumulative Probability Curves): Project completion date probabilities.
  • Torado Charts: Sensitivity analysis for durations (which activities drive project uncertainty).
  • Criticality Analysis: Determining "Criticality Index" (how often an activity is on the critical path).
  • Risk Driver Analysis: Identifying the top risk events impacting the schedule.
  • Understanding the "True" Critical Path.
• Analyzing Schedule Contingency: Probabilistic determination of schedule contingency.
• Laboratory Session: Running QSRA on the prepared project, interpreting the S-curves, tornado charts, and criticality index reports to identify key schedule drivers and probabilistic completion dates.

Day 4: Quantitative Cost Risk Analysis (QCRA) & Integrated Analysis with PRA

• Modeling Cost Uncertainty in PRA:
  • Cost elements vs. schedule activities.
  • Applying probability distributions to cost estimates (e.g., direct costs, indirect costs, overheads).
  • Correlating cost uncertainties.
• Linking Risks to Project Costs:
  • Assigning discrete risk events from the risk register to specific cost elements.
  • Defining the impact of risk events on cost items.
• Performing Quantitative Cost Risk Analysis (QCRA):
  • Setting up the cost analysis parameters in PRA.
  • Executing the cost simulation.
  • Interpreting Cost S-Curves and Cost Tornado Charts.
• Integrated Cost and Schedule Risk Analysis:
  • Combining QSRA and QCRA in a single simulation.
  • Understanding the interdependencies between schedule delays and cost impacts.
  • Interpreting integrated S-Curves for time and cost.
• Contingency Determination (Cost): Probabilistic determination of cost contingency based on desired confidence levels.
• Practical Exercise: Setting up cost uncertainty and risk events for the project, running an integrated cost and schedule risk analysis, and deriving probabilistic cost and schedule contingency.

Day 5: Risk Response Planning, Optimization & Reporting in PRA

• Risk Response Planning in PRA:
  • Mitigation Strategies: Modeling the impact of response plans (e.g., reducing duration uncertainty, eliminating risk events).
  • Cost-benefit analysis of mitigation options.
  • Developing contingency plans
• Optimization of Risk Responses: Running "what-if" scenarios in PRA to compare the effectiveness of different risk responses.
• Sensitivity Analysis (Advanced):
  • Using PRA's tools to drill down into key drivers.
  • Scenario analysis for strategic decision-making.
• Reporting and Communication of Risk Analysis Results:
  • Generating professional risk reports from PRA: Summary reports, S-curves, tornado charts, risk register.
  • Tailoring reports for different audiences (executive, project team, stakeholders).
  • Communicating probabilistic outcomes and risk exposure clearly.
• Integrating PRA with Project Control Processes:
  • Using PRA results for baseline management.
  • Supporting risk monitoring and control.
  • Lessons learned from risk analysis.