Risk factors are way to assign uncertainties due to specific sources. Normally uncertainties are assigned to schedule or costs using three point estimates (low, most likely, and high). These uncertainties represent aleatory risk: uncertainties due to natural variance that cannot be managed. However, similar to parametric methods, there can be multiple sources of this aleatory risk that can be identified and quantified using ranges with statistical distributions. In this way, factors share characteristics of both uncertainties and risk events. Like uncertainties they have 100% probability of occurring and like risk events that are due to specific causes.
The value of risk factors is that it provides a method to model variance due to known or common sources of uncertainty such as network performance or throughput, organization capability, or other external or internal factors.
The goal of using risk factors is that it will improve the modeling of uncertainties and possibly provide insight into how specific sources of project uncertainties or systemic uncertainties could be reduced through implementation of best practices.
In RiskyProject, factors are modeled as risks with 100% probability that are assigned to specific resources or activities in the schedule. In the example below, the Risk Factor “Productivity” has been assigned to a work package “Foundation” that includes multiple sub-tasks.
When you run a simulation, this factor will be accounted for in the results. Further, it will possible to identify the factors contribution to the overall variance in the project parameters (finish time, cost, duration, etc.) and as mentioned can identify the most significant sources of uncertainty and what they should focus on to improve performance in the future.