The Importance of Human Resource Forecasting in Project Management

Abstract

The research explores HR forecasting methods in project management specifically for Nigeria’s banking and telecommunications sectors. Project management requires HR forecasting tools to connect employee qualifications with project requirements because of accelerated technology development and fluctuating employment markets. Several shortcomings exist regarding methodological advancements as well as the inclusion of stakeholders together with the implementation of artificial intelligence (AI) technologies. Project success rates and workforce efficiency together with stakeholder satisfaction along with organizational barriers receive evaluation through this research which relies on 278 surveys from HR and project managers. Historical trend analysis and managerial judgment continue to dominate forecasting methods because organizations remain familiar with their methods while predictive analytics solutions powered by AI demonstrate only moderate implementation despite their potential benefits. Organizations that bring together AI systems and human judgment achieve greater success in projects and earn more satisfied stakeholders. The level of accuracy in forecasting directly enhanced how optimally organizations could utilize their workforce demonstrating the importance of data-based planning. Data quality problems together with employee reluctance to transform operations proved to be the biggest obstacles for effective forecasting rather than budget limitations. The research demonstrates weak stakeholder theory compliance because employee needs and diversity targets received inadequate attention while showing partial support for contingency theory through situation-specific modifications. The research expands theoretical knowledge by demonstrating the validity of contingency theory for forecast adaptability and it tests the implementation feasibility of stakeholder theory. The practical use of this research demonstrates that organizations need to develop mixed forecasting systems along with strong data protection systems coupled with adequate organizational preparedness to accept new technologies. The advisory calls for the integration of AI systems combined with stakeholder-led processes and regular model assessment to improve agility. The research fills a fundamental hole in HR forecasting literature through its empirical findings from developing economies which deliver operational strategies to enhance workforce planning during project volatility.
Keywords: Human Resource Forecasting, Project Management, Artificial Intelligence, Contingency Theory, Stakeholder Theory, Nigeria.