IT Project Risk Assessment Using Principal Component Analysis

Risk assessment, a critical process for project evaluation and investment, is one of the most important steps in IT projects implementation. Current qualitative and quantitative methods include analytic hierarchy process (AHP), artificial neural network (ANN), causality analysis, fuzzy comprehensive evaluation, etc. But most of them suffer from one of these two shortcomings: 1) the evaluation process is too subjective; 2) the calculation process of risk assessment is too complicated. In this paper, we proposed an IT project risk assessment model using principal component analysis. It could evaluate the risk with limited input data, clear indicator for stakeholders and within satisfactory calculation time. This model provides a more simple way to avoid risk for IT analyst and experts. An experiment was demonstrated to show the validness of this method.