If you have been among the millions following my blog for the past few years, you know that I’m a fan of a disciplined approach to both qualitative and quantitative risk analysis as a tool to manage schedule and budget risk in project management.
Most often, risk analysis is seen as a tool used at the start of a project to gauge schedule and cost risk, or to assess the potential downside in a failing project. It is very helpful in these scenarios.
However, I’ve been persuaded that deterministic schedules and budgets are nothing more than fictive numerology masquerading as precision science. The level of precision detailed in a multi-year, level 3 project schedule is not, in reality, obtainable knowledge. One cannot possibly know that the 23rd of November, two years from now will be the exact day on which we will finish the project. What one can know is the probability of completing on November 23. It just seems more honest and transparent to me.
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So, let’s start managing our projects using the best information we can. If we run Monte Carlo simulations on a monthly basis, we can track and watch the probability of completion of the project on the deterministic date. As change orders are approved and integrated into the project network, we can see how they impact the probability of completion on the deterministic date.
Some changes will likely create new critical paths within the network. Within the thousands of iterations created during a simulation, multiple potential future critical paths can emerge. As a project manager, wouldn’t you want to have this information months, or years ahead of the actual change in your project’s critical path?