Enhancing Resource Allocation in IT Projects: The Potentials of Deep Learning-Based Recommendation Systems and Data-Driven Approaches

The dynamic landscape of Information Technology Project Management (ITPM) along with a recent emphasis on the concept of suitability, motivates organisations to better utilise their resources and improve current practices. This has been leading to explore the potential of deep learning-based Recommendation Systems (RecSys) in this domain. We focus on critical aspects of Agile Project Management, resource allocation, and performance monitoring. Our study also evaluates RecSys’ effectiveness in enhancing project allocation and overall project success rates in ITPM. Analysing a diverse range of data, we observe a positive correlation between employee experience, skills, and project allocation ratings. The findings suggest that these variables exert a greater influence than traditional factors like age or educational background. We also demonstrate the benefits of leveraging historical performance data for future project planning and the utility of tracking ratings during project development. This paper contributes valuable insights for practitioners in IT project management, offering data-driven strategies to improve resource allocation and performance monitoring.