Project Management Efficiency using Soft Computing and Risk Analysis

Abstract

A software project in general involves the presence of risk and hence risk analysis is required.. Most software project managers do it informally and superficially, if they do it at all. The time spent identifying, analyzing, and managing risk pays itself back in many ways: less upheaval during the project, a greater ability to track and control a project, and the confidence that comes with planning for problems before they occur. The software project planner must estimate three things before a project begins: how long it will take, how much effort will be required, and how many people will be involved. In addition, the planner must predict the resources (hardware and software) that will be required and the risk involved. The basic objective of the paper shall revolve around the concepts on project management, soft computing and risk analysis techniques. The objective of this paper is to present an approach for creating a robust risks classifications and measurement system. This paper quantify the project management efficiency (PME) using a Soft computing tool based fuzzy logic system (SFLS) employing risk analysis. This approach indeed provides simplification and reduces the effort and time to perform an analysis for project selection. The evaluation of PME can serve for project managers and for project organization as indicator for the level of achievement of project management objectives. PME may help in the evaluation of performance of project teams.