Revolutionising Construction: The Role of Machine Learning in Project Success
OpEd – Dr. Neda Kiani Mavi
(Lecturer in Project Management, School of Business and Law, Edith Cowan University)
The construction industry is a key driver of economic growth, contributing 20% to Australia’s GDP. However, this sector often faces significant challenges, such as delays, cost overruns, and stagnant productivity, particularly in medium and large-scale projects. These issues can substantially undermine project success. To address these challenges, we have developed an innovative decision support system that leverages machine learning to evaluate the feasibility of construction projects with remarkable accuracy. By analysing key success factors and criteria, this system provides precise forecasts of project outcomes, reducing much of the uncertainty traditionally involved in construction planning.
Success in construction goes beyond merely completing a project; it involves meeting criteria such as stakeholder satisfaction, business profitability, and public benefits. Our system provides a strategic advantage by analysing the interactions of success factors, offering insights for timely interventions and informed decision-making.
Achieving success in construction is crucial. Successful projects lead to satisfied clients, enhanced reputations, and increased profitability. By accurately forecasting project success, our decision support system empowers sponsors and managers to manage current projects effectively and plan strategically for the future. This innovation marks a significant advancement for the industry, paving the way for more successful and efficient construction projects worldwide. The construction industry is poised for an era of greater innovation, improved efficiency, and unparalleled success. The potential transformation is immense, and the tools are now within reach to make this vision a reality.