Probabilistic Critical Path

Project management theory tells us that there is always a sequence of activities that ultimately determines the project duration. However, practice tells us something equally important: that sequence can’t be reliably predicted in advance.

Experience clearly demonstrates that the probability of the project’s Resource Critical Path changing during the project lifecycle is almost certain. This is not necessarily a result of poor planning. It happens because the actual delivery sequence that drives the completion date depends on factors that can’t be fully known in advance: resource availability and calendars, supply volatility, productivity, materialised risks, and uncontrolled aleatory uncertainties.

Instead of focusing on identifying and managing one supposedly most important path, the delivery team should focus on a cluster of activities that are likely to drive the project completion date.

Such a cluster can be identified through Probabilistic Critical Path analysis.

To calculate it, the project needs a dynamic delivery model that integrates project possibilities, uncertainties, dependencies, resource and supply limitations, and other real-world constraints. Advanced scheduling methods can then be combined with repeated random sampling to calculate how frequently each activity becomes delivery-critical across the range of possible project scenarios.

The result is not one deterministic critical path, but a probabilistic view of the activities and clusters most likely to influence the project completion date.

Advanced project delivery systems, like Spider Project, can calculate Probabilistic Critical Path already but project managers and planners need to learn how to develop a reliable simulation model.