Latent trait analysis for risk management of complex information technology projects

Abstract

Recent years have seen a major increase in the application of predictive analytics to the service delivery domain as more and more service providers rely on such analytics for proactive risk management. At the pre-contract stage, identifying potential project risks accurately is of vital importance since it allows service providers to avoid profit erosion through proactive risk management. This paper describes a data-driven approach to project failure prediction of complex information technology (IT) projects. We introduce a novel theoretical framework of Latent Trait Analysis (LTA), whose original form was first developed in psychometrics. We take as the input questionnaire data of risk assessment reviews in the quality assurance (QA) process of IT projects before contract signing, and attempt to predict the project health in the delivery phase after contract signing. The idea is to explicitly capture the human cognitive process through LTA, and estimate the latent project failure tendency hidden behind the questionnaire answers collected by QA experts. Using real QA data of an IT service provider, we demonstrate that our approach outperforms existing approaches in project failure prediction while providing practical information on the usefulness of individual question items.