A unified methodology for project planning risk

It is essential for project managers to be in a position to assess the costs and time involved in almost any project that has to be considered by their companies. The existence of their companies and institutions might depend on how accurate these assessments are and how they are used to quantify the risk involved in the venture. The thesis reviews the existing literature of risk assessment methodologies and evaluates the advantages and the disadvantages of the approaches which have been used. Many papers have been produced which have illustrated and explained most of the current methods and techniques used in the assessment of risk and also suggestions have been made about how and when to use these methods. Chapman, C. for example, has employed the "Controlled Interval" approach in his work over the last ten years, with only limited accuracy involved in his final estimates of the total time/cost of a given project. His co-operation with Cooper, D. has resulted in producing the "PERK" software package. We have fully examined and studied in this thesis other methodologies, like Functional and Numerical Integration, and some improvements have been suggested. Substantial work has been done on the Moments Method and further developments on the applicability of the method to parallel activities has been carried out. The accuracy of the estimates obtained with the use of Pearson's curves, has been investigated. The particular contribution of this work to Project Planning Risk Assessment involves the development and assessment of mathematical techniques which have been used in Project Management Planning. We develop an approach which is mathematically justifiable and practically feasible to project managers. A new Unified Methodology is tested and found to be appropriate in a variety of project management contexts. Our new approach -The New Unified Methodology- makes use of The Progressive Reduction Procedure to collapse activity networks and uses the first four moments of Erlang activity time distributions to fit Pearson curves to the distribution of project completion time.