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Features, Research & Analysis, Technology

Using predictive AI to improve decision-making and reduce risk

Karthik Venkatasubramanian

Automation efforts have quickened by many engineering and construction (E&C) organisations as the pressures felt from growing risk, strained supply chains, and narrowing margins continue to increase. To improve operations, traditionally organisations have used technology to refine processes and procedures, but putting the data collected from digitisation to good use can sometimes be an afterthought.

What if you could boost your chances of delivering a project on-time and on-budget by utilising the growing volume of data that you previously only saved for future reference? AI holds enormous potential to help organisations optimise their decision-making and to drive project success by proactively unlocking new predictive insights from project data.

Realise full potential with historical data

The construction industry is generating vast amounts of data as digitisation is being embraced, and with it, there is a significant opportunity for teams to learn from and use this data to create better estimates, plan smarter, and reduce risk.

Historical data provides a starting point for organisations to analyse their business. The ability to gain insights from historical data and apply them to current projects is key to creating organisational baselines and benchmarks which can help prevent the same mistakes from being repeated and ensure there is a focus on driving continuous improvements. At a minimum, it prevents the “copy from a past project and paste onto the current project” mindset, which can be common when team members are under time constraints.

Predictive AI through lead indicators

Until now, business intelligence (BI) technologies have generally focused on lag indicators, things that have already happened on the project. While these insights are valuable, new developments in AI can unlock a new level of project intelligence, where the focus is on lead indicators based on real-time data, driving predictive insights that can bring about better outcomes.

These AI technologies use machine learning (ML) to power active intelligence, helping organisations learn from their past data while continually assessing the present. This use of ML enables organisations to continuously monitor developments and adjust plans using predictive insights. For example, such a system can learn from historical schedule data and make predictions about potential delays on current projects. These systems become smarter over time with increasing data quality, improving in accuracy.

Improving predictions at work

Active intelligence yields predictive insights that add value to nearly every aspect of construction project management, including critical areas such as schedule, cost/budget, quality, safety, risk, and collaboration. AI can provide an effective early warning system that surfaces potential issues like project delays, cost overruns, defects and rework, etc. long before they boil over.

Active intelligence utilises rich internal and external data sources to continuously improve prediction accuracy. When combining these along with external data, such as weather forecasts/history, supply chain disruptions, and workforce disruptions, it is possible to create a more accurate schedule and manage them proactively to reduce risk.

 The Internet of Things (IoT) sensors and the rich data they can provide are additionally set to play a growing role with how active intelligence can improve quality of work, site safety, and tracking progress onsite.

There’s a lot that can be learned from the past, but the real benefit of active intelligence is in its ability to predict the future and make the decisions needed to change the course of a project before it’s too late. The challenge has been in demystifying some of the technologies and its associated jargons, integrating disparate data sources and reducing the time-to-value for the investment in these types of AI and ML initiatives. The adoption of these technologies will grow as owners and project delivery teams partner with organisations that solve some of these issues by providing predictive insights out-of-the box.

AI and ML are putting active intelligence within reach of the construction industry. With AI we can look ahead and improve the decision-making of tomorrow.

By Karthik Venkatasubramanian, vice president of data and analytics at Oracle Construction and Engineering

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