Using CPM for risk prediction
Change made to one part of a system tend to propagate between parts of that system according to the relationships between its parts. For instance, change made to the geometry of one component in a physical product may require adjacent components to also be changed, so they will still fit together. In turn, these changes may require yet more components to be changed. The propagation of change between related elements can also be observed in other types of system, such as processes, organisations, etc.
Change management can be supported by tools which predict the impact of a change, helping to identify the likely knock-on impact. For instance, this might reveal high-risk connections that need to be carefully managed, might help with scheduling the execution of the change process, or might reveal that a given change is just too expensive to be worth implementing at all.
Various tools have been proposed to assist such prediction, but few (if any) have been evaluated in quantitative terms, either in an experimental or real-life setting. We therefore developed a simulation model to evaluate the impact of different change prediction capabilities upon the efficiency of the redesign process.
This tutorial describes