Identifying cost, schedule, and performance risks in project planning and control: A fuzzy logic approach.

Abstract

A review of risk identification and quantification methods revealed the need for additional methods to assess cost, schedule, and performance estimation. A risk model was developed using fuzzy set theory. The risk model was tested using a sample radar development project. The results obtained from the model proved that a practical approach incorporating subject-matter expert assessment and fuzzy set theory could be used to both identify and quantify project risks. Outputs from the model had sufficient fidelity for decision-makers to determine areas for additional surveillance and/or control.

In a "real" project management environment historical cost, schedule, and performance data are often not available. The lack of historical data requires the estimation of cost, schedule, and performance parameters. The uncertainties associated with parameter estimation results in inherent project risks. The identification and quantification of project risks associated with parameter estimation requires analytical tools that are effective and usable in project planning and control.