Project Risk Assessment
Fuzzy Logic Approach to Project Risk Assessment
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In this better, faster, and cheaper era, project managers face many challenges in their attempts to perform effective project management. Too many projects suffer because the cost, schedule and performance goals are unachievable. Unrealistic cost, schedule, and performance estimates and a failure to quantify and communicate the uncertainty of these estimates to managers and stakeholders often results in project failure. A systematic risk identification approach using expert judgment coupled with a risk quantification method has utility in project planning and control. Cost, schedule, and perfo...
In this better, faster, and cheaper era, project
managers face many challenges in their attempts to
perform effective project management. Too many
projects suffer because the cost, schedule and
performance goals are unachievable. Unrealistic
cost, schedule, and performance estimates and a
failure to quantify and communicate the uncertainty
of these estimates to managers and stakeholders
often results in project failure. A systematic risk
identification approach using expert judgment
coupled with a risk quantification method has
utility in project planning and control. Cost,
schedule, and performance are regarded as
the "magical" combination that is continuously
reviewed by project managers. These three factors
form the basis for project control. Therefore, to
achieve project success, each of these factors must
be understood and properly estimated. A risk
assessment model was develop using fuzzy membership
sets. The model identified and quantified project
risks associated with all three of the project
parameters considering risk likelihood and the
resulting potential consequences on project
estimates.
managers face many challenges in their attempts to
perform effective project management. Too many
projects suffer because the cost, schedule and
performance goals are unachievable. Unrealistic
cost, schedule, and performance estimates and a
failure to quantify and communicate the uncertainty
of these estimates to managers and stakeholders
often results in project failure. A systematic risk
identification approach using expert judgment
coupled with a risk quantification method has
utility in project planning and control. Cost,
schedule, and performance are regarded as
the "magical" combination that is continuously
reviewed by project managers. These three factors
form the basis for project control. Therefore, to
achieve project success, each of these factors must
be understood and properly estimated. A risk
assessment model was develop using fuzzy membership
sets. The model identified and quantified project
risks associated with all three of the project
parameters considering risk likelihood and the
resulting potential consequences on project
estimates.
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