Construction productivity improves when project data stops sitting with individual players and starts working across the full build ecosystem.
Construction has talked about productivity for years. The harder question is what actually shifts it.
Kurt Brissett argues that the answer sits less in isolated tools and more in how data is structured, shared, and applied across the full project lifecycle.
For Built, that means using digital engineering to reduce project risk, improve procurement and supply chain efficiency, and make collaboration stronger across a crowded ecosystem of clients, subcontractors, regulators, and government.
Key takeaways:
- Construction teams get more value from digital tools when project data becomes a shared working environment, rather than staying trapped inside separate stakeholders or systems.
- 3D models become far more useful when they are enriched with live construction data, giving teams a stronger basis for rehearsal, coordination, and earlier risk reduction.
- Industry productivity lifts when project insights are reused across bids and builds, helping teams benchmark performance, reduce rework, and improve sustainability over time.
Shared project data makes construction decisions stronger
Digital tools become more useful in construction when they give teams one place to work from, rather than another fragmented layer to manage.
That is what turns technology from a nice capability into a delivery advantage.
Kurt points to the three dimensional model as the heart of that shift.
At Built, those models are increasingly being augmented with construction related data sets and used as a single source of truth for collaboration across internal teams, clients, and subcontractors.
That gives teams a stronger basis for coordination and makes it easier to de risk elements of the build before they turn into larger schedule or cost issues.
Better planning starts with earlier rehearsal and clearer visibility of risk
A digital environment earns its place when it helps teams see issues sooner, rehearse more effectively, and make higher value decisions before work becomes expensive to unwind.
That is where AI starts to have practical weight in construction.
Kurt links that directly to scenario based rehearsals and design support.
He explains that AI can help teams focus attention on the areas that matter most during construction, while richer modelling can improve sequencing, manage weather related risk, and reduce rework and material waste.
In that sense, the value is not only operational. It also reaches cost control, schedule reliability, and sustainability outcomes across the life of the build.
Industry productivity rises when data survives the project
Construction will keep losing productivity if each project learns in isolation.
The bigger opportunity comes when delivery data is carried forward, compared across jobs, and used to improve the next bid and the next build.
That is one of Kurt’s clearest points.
He says the sector has historically done a poor job of leveraging data because too much of it stays siloed within individual players.
Built is trying to push further into a common digital environment where stakeholders can collaborate earlier, burn down risk, and work through cost planning and estimating more efficiently.
Just as importantly, Kurt sees real value in benchmarking across past projects so teams can learn what worked, what did not, and apply those lessons to future tenders.
That is the kind of feedback loop that can lift productivity across the wider industry, not just within a single project team.