Quantitative Project Risk Analysis
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The document presents a framework for quantitative project risk analysis developed by Intaver Institute, aimed at improving project decision-making while addressing common issues like project delays and budget overruns. It emphasizes the integration of quantitative methods into project management to provide accessible and user-friendly tools, alongside training and consulting services. Key methodologies discussed include Monte Carlo simulations, risk event modeling, and sensitivity analysis to identify critical risks and uncertainties in project schedules.
Quantitative Project Risk Analysis
- 1. Quantitative Project Risk Analysis 1 Intaver Institute Inc. 303, 6707, Elbow Drive S.W., Calgary AB Canada T2V 0E5 www.intaver.com
- 2. Agenda • Introduction • Part One – Project Decision Framework – Quantitative Analysis within Project Risk Management • Part Two – Practical Exercises • Q and A 2
- 3. Introduction Who is Intaver Institute? – Formed 2002 – Group of risk, economic, and decision analysis experts – All to some extent were involved in developing software tools for these fields 3
- 4. Problem • Many IT projects were late or over budget • No readily available tools for the analysis of project schedules, the provided similar analysis as the ones they were developing for other industries • Decision analysis processes including quantitative analysis widely used in many industries, but not project management – Many project manager don’t believe in benefits of quantitative methods – Most methods and tools remain relatively complex, require special training, and expensive 4
- 5. Vision: Quantitative project analysis for the rest of us 1. Develop application – No specialist training required to get started – Easier to use and understand – Relatively inexpensive 1. Provide project decision analysis training and consulting to support application 5© Intaver Institute 2009
- 6. Part One: Project Decisions Framework and Quantitative Analysis • Project Decision Analysis • Quantitative Project Risk Analysis and Management 6
- 7. Project Decision Analysis • Successful projects are the result of good decisions • Structure decision analysis – Well defined process founded in decision analysis science – Applicable to project management – Provides framework that will improve project decisions 7 Decision Analysis vs. PMBOK • Decision analysis not in conflict with PMBOK • Can be easily integrated (as needed) into current PM
- 8. Risk Analysis Pyramid 8 Quantitative Analysis Qualitative Analysis Risk Management Planning © Intaver Institute 2009 8
- 9. Quantitative Estimates • Uncertainties – 3pt estimates – Distributions • Risk events – Chance – Outcome – Result – Moment of risk 9© Intaver Institute 2009
- 10. Types of uncertainties • Duration • Cost • Start and Finish Times • Lags • Rates and Resource Allocation • Entered as 3 pt estimate 10© Intaver Institute 2009
- 11. Types of Risk • Task • Resource • Global (project or local) 11© Intaver Institute 2009
- 12. Risks or uncertainties? • Use uncertainties in cases where you have historical data that is both strong and analogous • Use uncertainties in cases where you have some historical data and strong expert opinion (experts have consensus) • Use risk events when little historical data exists to back up expert opinion • Use risk events on higher risk projects • You can use a combination of risk events and uncertainties 12
- 13. Risk or uncertainties • Risk events are less prone to the effects of human biases and heuristics • Easier to recall effect of risk events on projects 13
- 14. Event Based Analysis • Risk event estimates less affected by heuristics and biases • Risk events estimates easier to obtain via relative frequency analysis • Event based analysis of causes of project uncertainty – Sensitivity analysis can be done to identify critical risks – Uncertainties require additional root cause analysis to identify critical risks 14
- 15. Modeling Risk Events • Chance - % chance that the risk will occur • Outcome – relative % or fixed (e.g. % cost increase, Fixed delay) • Result - 15% • Example Fire: 20% Chance of a Fixed Delay of 14 days • Risks can have mutually exclusive alternatives 15
- 16. Monte Carlo Analysis • Statistical sampling • Runs many simulations of a project that produces probabilistic distributions of particular results (cost, duration, finish time, etc.) • Gaining popularity as size and power of hardware and software improve 16
- 17. Project Risk Analysis • Create project schedule • Define project uncertainties • Define project risks • Perform Monte Carlo Simulations • Analyze results 17
- 20. Results of Analysis • Project outcomes with and without risks and uncertainties • Sensitivity analysis • Cost analysis • Identifying critical risks and uncertainties • Success rates 20
- 21. Project Summary 21 Main Project Parameters with and without risks Probabilistic results
- 22. Result Gantt Chart 22 White bars represent original project schedule (no risks) Blue bars represent project schedule with risks Because of risks, project duration has significantly increased
- 23. Detailed Results of Analysis 23 Move the slider to determine the chance that project will be within budget Get detailed statistical data You may export this data to other software it graphic or text formats Detailed results can be shown for each tasks or whole project for cost, duration, start time, finish time, and income.
- 24. Cost Analysis You may compare cash flow with (blue line) and without (red line) risks Cash flow is generated based on fixed and variables cost and income associated with tasks and resources
- 25. Crucial Tasks Crucial tasks have the most affect on the project schedule Green bars represent tasks uncertainties in which almost not affecting project schedule Crucial tasks for project cost and duration can be different
- 26. Critical Risks Tornado chart shows the risks that have the most affect on the project schedule Critical risks need to be mitigated first
- 27. Project Dashboard 3x3 3 most important project parameters (cost, duration, and finish time) 3 most crucial tasks 3 most critical risks Project Dashboard 3x3 is a condensed view for most important results of analysis
- 28. Risk Chart The risk chart shows risk uncertainty for tasks versus duration or cost This task has low duration but high risk These tasks have balanced risk versus duration ratio.
- 29. Success Rate The deadline is causing calculation of the task in 86% of cases A task can be canceled if it reaches a task or a project deadline or if it is affected by risk with a “Cancel task” outcome. This task is affected by one of many risks with impact “Cancel task” Success rate is calculated based on number of times the task is not canceled
- 30. Tracking This task is 100% completed (green bar) For each task at any moment you may enter how much work has been completed This task is partially completed (yellow bar) Risky project automatically adjust probability of risks for partially completed tasks
- 31. Tracking Results New project forecast is done each time actual project data is entered Original (baseline) project duration Actual project duration Low, base, and high forecast
- 32. Intaver Institute 32 Intaver Institute performs project risk management, risk analysis, and decision analysis training and consulting Download a trial version of RiskyProject at: http://www.intaver.com/index-downloads.html (version 2.1) White papers, presentations : http://www.intaver.com/index- whitepapers.html Courses: http://www.intaver.com/riskyproject_training.html
- 33. Future Reading Lev Virine and Michael Trumper Project Decisions: The Art and Science Management Concepts, Vienna, VA, 2007 Lev Virine and Michael Trumper Project Think: Why Good Managers Make Poor Project Choices Gower, 2013
Editor's Notes
- #7: Bring out parking lot questions
- #13: So what should we use.
- #15: Risks are separated from the schedule and cost. When we use distributions, we set “boundaries” on them. Risk events less effected as we do not know the statistical outcome until Monte Carlo is run. Less conscious or unconscious “gaming” of estimates.