In this regard, Khodakarami et al. report that, "Critical path method is very simple and provides very useful and fundamental information about a project and its activities schedule. However, because of its single-point estimate assumption, it is too simplistic to be used in complex projects" (p. 41). The authors' extensive use of acronyms, though, makes it difficult to understanding some of their more esoteric descriptions of the integration of critical path methods into Bayesian networks notwithstanding their use of illustrative graphics in support of their assertions. Despite this constraint, the authors describe several aspects of their innovative approach that can contribute to project management in several ways, including the following. Project Integration Management

Project integration management involves the processes required for overall project coordination (Kendrick, 2003). The methodology developed by Khodakarami et al. allows for the development of various "what-if" scenarios that can model the effects of different processes at different points in time (Khodakarami et al.).

Project Scope Management

The methodology developed by Khodakarami et al. may be less useful for project scope management applications. In this regard, project scope management describes the project processes that are required in order to ensure that the project "defines the deliverable(s) and that it includes all the work required, and only the work required, for successful project completion" (Kendrick, 2003, p. 10). The work breakdown structure of the critical path method...

The methodology described by Khodakarami et al. reportedly models uncertainty and its effects on the duration of any given activity and provides the ability to keep track of delays that may affect the time required for project completion.
Conclusion

The research showed that the critical path method is among the most widely used project management approaches today. One of the major constraints involved in the use of the critical path method, though, is the inability to integrate uncertainty, a constraint that is directly addressed by the integration of Bayesian networks with the critical path model. The model developed by Khodakarami et al. remains untested in real-world settings, though, and the authors concede that more research will be needed before these techniques can be scaled up to satisfy the requirements of project managers in the future.

References

Kendrick, T. (2003). Identifying and managing project risk: Essential tools for failure-proofing your project. New York: AMACOM.

Khodakarami, V., Fenton, N. & Neil, M. (2007, June). Project scheduling: Improved approach to incorporate uncertainty using Bayesian networks. Project Management Journal, 39-49.

Lauren, B. (2008, May). The case for e-project management. ABA Banking Journal, 100(5),…