Development of Machine Learning Models for Prediction of IT project Cost and Duration

Abstract

Despite the impact of the COVID-19 pandemic in 2020-21, the digital economy remains solid and sustainable. This trend continues to drive massive demand for Information Technology (IT) projects. Underestimated costs and time are considered one of the most critical IT project risks that directly impact a project's success or failure. Currently, there is a lack of models, tools, and techniques capable of effectively predicting cost and duration. This study aims to find a solution to enhance prediction capability by using a machine learning (ML) model. An experiment was conducted comparing the performance of each ML model utilizing three distinct datasets and fourteen different models against six performance indicators. The results indicated the existence of a highly reliable, effective, consistent, and accurate ML model with a significant degree of augmentation compared to conventional predictive project management tools and techniques.