Artificial intelligence and machine learning will revolutionise budgeting and scheduling on complex construction projects, a leader in technology says.

In a recent interview with Sourceable, Rob Bryant, EVP, Asia Pacific at multi-national construction project management software firm InEight, said that artificial intelligence (AI) and machine learning will deliver multiple benefits when preparing budgets and schedules for major civil developments.

According to Bryant, construction projects face challenges from variables such as materials, labour, changing regulatory requirements and processes, all presenting risk

He says technology can help by providing greater project visibility.

This can help in two ways.

First, greater visibility can help to identify anything which may cause delays and need to be corrected, mitigating many of the risks inherent in projects today

Where delays are likely to occur on account of material supply, for example, visibility about the likely impact of this can enable rescheduling of labour to prevent people from arriving on site without the materials which are needed to conduct work.

As the project progresses, greater visibility can help to track performance against budget and make adjustments to prevent money being spent in excess of what has been allocated.

Second, better visibility promotes greater trust and collaboration.

For project owners, visibility through statistics and reports enables them to evaluate progress without needing to second-guess the head contractor.

For others such as subcontractors, having projects run more smoothly through better visibility provides greater assurance of their ability to commence work at the scheduled time and that there will be sufficient funds for them to be paid.

Speaking about AI, Bryant says its main use when applied to construction project data is to compute a multitude of data points and bring these together to facilitate easier and better-informed decision making.

The main areas of application are budgeting and scheduling.

In these applications, AI can draw upon historic data and develop a series of scenarios based on outcomes which have been achieved in the past.

When preparing a schedule, for example, the software will recognise schedules and results from similar projects undertaken in the past and make suggestions about the amount of time be applied for permitting authority approvals or material movement.

This then enables project managers, owners and other stakeholders to select budgets based on preferences and priorities regarding delivery timeframes, budgets and project risks.

Use of AI in this process has several benefits.

These include:

• Saving time in budget and schedule preparation by automating manual work.
• Enabling project teams to produce better and more accurate budgets and schedules which draw upon past project experience and outcomes. This includes outcomes both on projects that have been delivered on time/on budget along with those which have not. This is done in a way which leverages data across the organisation and does not rely upon individual manager experience.
• Assisting project teams to transform budgeting and scheduling into a dynamic process which is updated and maintained throughout the project to provide a realistic view of where projects are heading. This is important as in the past, budgeting and scheduling have often been static events which are completed at the commencement of projects before things go offline after that.
• Better collaboration and trust. Once budget and schedule scenarios have been generated, these can be shared with stakeholders in a way which promotes collaboration in decision making and greater trust in the project manager/head contractor concerned from project owners.
• Establishing a point of difference for contractors when bidding for work as project owners will have greater confidence in their ability to deliver on time and within budget.

Bryant says leveraging historic data to guide future actions is powerful.

“The way I like to think about it is that a lot of the data points throughout the life of the project help you to look in the rear-view mirror and understand what was achieved and how much was spent,” Bryant said.

“But if you take that data and overlay it with your forward schedules and your budget, you can start to use it to make informed decisions about the future.

“That’s when you get real value – future looking decision making.”

Bryant’s comments come as the construction industry both locally in Australia and internationally is gearing up to deliver on a large volume of public infrastructure projects.

In Australia, forecasters such as BIS Oxford Economics expect the dollar value of work done on road and rail projects to reach record levels in coming years.

The comments also come amid concern over projects meeting delivery expectations.

In a worldwide survey which InEight conducted last year, only 48 percent of project owners and contractors expressed confidence in their ability to deliver work on time and within budget on a consistent basis.

Asked about the role of software providers, Bryant says vendors such as InEight are working with contractors and owners to help them to capture project data and develop optimal ways through which to use their data.

Contractors can then establish templates, approaches, decision points and collaboration methodologies to best suit their own needs.

Speaking particularly of InEight, Bryant says AI/machine learning functionality has been built into the firm’s planning, scheduling and risk solution to enable users to view scenario-based events and to provide suggestions about potential approaches.

He says the biggest appetite for AI/machine learning has been in scheduling.

Beyond that, organisations are exploring how risk can be more effectively managed through the scheduling tool along with how this can be extended to contract management with the various vendors and contractors.

Another growing area of interest is in estimating with alternate scenario modelling.

Bryant says interest in AI/machine learning is growing rapidly.

“There are an increasing number of organisations out there who understand that these solutions are there for their benefit,” Bryant said.

“The challenge for organisations is their readiness to transform and adopt.”