A new system could enhance the success rates of medium and large-scale construction projects. 

An initiative from experts at Edith Cowan University (ECU) aims to eliminate the guesswork in evaluating project feasibility, by applying a machine learning decision support system.

The system forecasts the success of construction projects by identifying and analysing critical success factors and criteria. 

ECU’s Dr Neda Kiani Mavi has identified 19 success criteria, organised into five clusters: project efficiency, business success, impacts on end-users, impacts on stakeholders, and impacts on the project team.

“Our findings reveal that project efficiency holds the highest importance, followed by impacts on the project team and stakeholders,” said Dr Kiani Mavi. 

“Within project efficiency, effective risk management is ranked as the most crucial criterion. This enables organisations to manage and monitor risks effectively by employing strategies such as resource reallocation.”

Her research indicates that large construction projects exceeding $200 million often exceed their budgets by over 30 per cent, with 77 per cent lagging behind schedule by more than 40 per cent. 

These setbacks are often due to ineffective risk management practices. 

However, efficient operations management can enable construction companies to achieve profit margins ranging from 20 per cent to 30 per cent.

In Australia, the construction industry is a significant economic contributor, accounting for approximately 20 per cent of the nation's GDP, which totals over $2.85 trillion. 

The Australian Construction Industry Forum (ACIF) forecasts a 5 per cent growth in the building and construction industry for 2023-24, increasing the value of work to $298 billion. 

Despite this growth, the industry faces challenges such as rising inflation, high interest rates, and industrial relation changes.

“Despite its vital role in the economy, the construction industry faces numerous challenges that significantly impact its success,” Dr Kiani Mavi says. 

“The inherent complexity and uncertainty of construction projects make them difficult to manage, even for experienced project managers.”

Dr Kiani Mavi also highlighted stagnant productivity growth and increasing pressures related to risk management as major issues. 

Over the past three decades, Australia's productivity in the construction sector has been persistently poor, resulting in an estimated $47 billion in lost opportunities.

According to the 2023 KPMG Global Construction Survey, 87 per cent of project managers struggle with project performance, often dealing with schedule delays and cost overruns. 

Additionally, only 50 per cent of project owners meet completion deadlines, primarily due to effective risk management strategies.

Dr Kiani Mavi’s decision support system analyses the interrelationships among critical success factors and criteria to forecast project success. 

She says early introduction of the application allows for timely interventions, mitigating potential delays, cost overruns, and other issues.

“When contractors, sponsors, owners, and project managers understand whether a project is more or less successful than previous similar projects, they can address the weaknesses and improve the strengths,” Dr Kiani Mavi said. 

“Successful projects lead to satisfied clients, enhanced reputations for companies, and increased profitability. On the other hand, project failures can result in financial losses, legal issues, and damage to a company’s reputation. Given this, understanding and achieving project success is crucial for project sponsors who aim to control both current and future projects. So, forecasting project success is not just beneficial but essential for the industry.”

Dr Kiani Mavi’s research is published in the International Journal of Construction Management and Engineering, Construction and Architectural Management.