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As the construction sector becomes increasingly rich with data, it’s become clear the winners will be the architects, engineers and constructors who capture the most meaningful data and exploit it most effectively.

That was the major takeaway from a recent presentation at the Buildings Show in Toronto hosted by Autodesk data and analytics consultant Nathaniel Coombs. The session was billed as Developing Data Literacy across the AEC Workforce.

With the surge in tech adoption comes a goldmine of information waiting to be understood and utilized, Coombs said.

“The more data you have, the more data you are capable of producing,” he said.

“Why is everyone building data centres? Because everything we do now creates a piece of data. It’s part of that continuum, the huge amount of data that engineers and architects are using, and it’s changing the world.”

Big competitive advantage

Research from Autodesk has shown mining and using data can become a competitive advantage for any AEC firm.

There’s a 56-per-cent increase in average profit growth rate between data capability leaders over beginners, and a 2.7-per-cent increase in expected average profit each year.

Unfortunately, many AEC firms are still closer to the beginner’s stage. Deloitte found the average construction company makes decisions based on only three data types among 11 studied.  

“I promise there is data in the back end of what you’re doing or that you’ve created along the way (that is not being used),” Coombs said. “These things lead to uninformed decisions, inefficiency, rework.”

Mine the right data

Every employee and executive should be engaged in collecting data, without exception, Coombs said – and it’s got to be the right data, he said: “Garbage in, garbage out is a common phrase.”

The engineer gathers BIM information, geographic and spatial inputs, project scope details and bid requirements; the estimator relies on model quantities, local cost figures, labour rates and bid specifics; the project manager tracks schedules, quality records, safety logs and labour activity; the operator monitors asset conditions, maintenance needs and production outputs; and the manager reviews financial results, business benchmarks and overall project performance.

Benchmarking includes determining how leadership views project health; planning suggests determining what questions the user is attempting to answer; and collecting includes ensuring it’s easy for end users to avoid making mistakes while inputting data.

“Data science combines math and statistics, specialized programming, advanced analytics, AI and machine learning with specific subject-matter expertise to uncover actual insights hidden in an organization’s data,” said Coombs. “This can be used to guide decision-making and strategic planning.”

Steps in a data implementation plan can include plan, collect, track, make a maturity assessment, revamp, organize, document, build a dashboard and train.

“You can’t do any of the AI stuff, any of the big data stuff, any of the real world-changing analytical work, without having a foundation,” said Coombs.

“There’s so much of it, that’s the thing, the amount of it has changed drastically in the last decade.”

The best advice for an AEC firm just embarking on a commitment to leverage more data, Coombs said, is to start simple. A user does not need a degree in data science to use a template or ask an AI tool questions.

Coombs highlighted the following tools and platforms – a list that includes Excel, from an older generation but still “very good at being a database,” he said:

• Power BI: Visualizes project data for cost and schedule tracking
• Microsoft Fabric: Unifies construction data sources (ERP, BIM, Procore, sensors) for advanced analytics
• Excel: Calculates estimates and engineering values with spreadsheets
• Tableau: Builds interactive dashboards showing real-time project performance
• Hex: Enables collaborative analysis of construction datasets and reports
• Looker: Centralizes project metrics for team reporting
• Domo: Integrates jobsite financial and scheduling data
• Amazon QuickSight: Delivers scalable analytics for multiple projects
• Autodesk ��������ion Cloud: Connects drawings models and field data

“I stress the importance of using data to make better decisions around projects,” said Coombs. “A little bit goes a long way.”