Quantitative risk analysis techniques including Monte Carlo simulation and probability distributions
Want to understand project risk without getting lost in heavy math? This page brings together a practical series of articles that explain Monte Carlo simulation in plain language, then gradually move into deeper topics like dependencies, automation, dashboards, and cost risk. Start with the basics, then work your way toward […]
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You’re in a steering committee meeting. The sponsor wants one date for the board deck. Finance wants to know when costs will hit. Operations needs to plan handoffs. And someone turns to you, the project manager, and asks the question that sounds simple but never is: “So when will we […]
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Project schedules usually look calm on paper. A few tasks, a few dates, a few arrows connecting one deliverable to the next. Then one team slips by three days, another waits for an input that is “almost done,” and suddenly a neat timeline turns into a traffic jam. That is […]
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Most project teams do not have a shortage of schedule data. They have a shortage of timely signals. A planner updates the file, a project manager looks at the critical path, and everyone hopes the finish date is still safe. The problem is that hope is not a control system. […]
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If you have ever walked into a steering committee with a risk report full of red, amber, and green flags, you already know the limitation. Stakeholders rarely want a static snapshot. They want to ask questions. What is the chance we finish by the board date? How much confidence do […]
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Most project leaders hear two different risk stories. One story is about time: Are we likely to finish by the target date? The other is about money: Are we likely to stay inside the approved budget? Those conversations often happen in separate meetings, with separate charts, and sometimes with separate […]
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You have the theory. You understand the math of the triangle. You have seen how a Tornado Chart can pinpoint your biggest threats. But in the real world, you are not managing three tasks in a vacuum. You are managing dozens, sometimes hundreds, in a complex project schedule. The biggest […]
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If you have been following this series, you now know how to use Monte Carlo simulation to predict your project’s finish date. You have seen the S-Curve, and you know how to find your P90 ‘Safe Zone.’ But as a project manager, knowing when you might finish is only half […]
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Have you ever wondered why, in a Monte Carlo simulation, a simple triangle can predict the future? It feels like a magic trick. You give the computer three numbers—Optimistic, Most Likely, and Pessimistic—and it spits out a range of possible dates. But if you look under the hood, it isn’t […]
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If you have spent any time in the world of project risk management, you have likely run into two heavyweight contenders. In one corner, we have the reliable, straightforward Triangular distribution. In the other, the sophisticated, smooth-curved Beta (or PERT) distribution. Choosing between them can feel like a philosophical debate. […]
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