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Data & AI for construction
Every construction project generates data, but hardly anyone looks at it while the project is under way.
Cost estimates, schedules, procurement, time records and equipment data sit in separate systems and spreadsheets. As a result, it is often only during the final cost review that you see where a project lost money. Data and AI bring these sources together and show where a project is going off track while there is still time to act.
Challenges,
Tight margins, staff shortages and projects increasingly awarded on price leave construction vulnerable to surprises. A subcontractor arriving late, idle equipment or a quantity that differs from the estimate has a direct impact on the bottom line. That calls for project-specific information while work is still under way.
How we support you,
We bring cost estimates, schedules, procurement and site records together in one data foundation. We then build reports and models that show where each project is deviating from the plan. These are some examples of what is possible. The right solution always depends on the challenge and the organisation.
DSL in numbers,
40
Data experts
10+
Years of experience
200+
Projects completed
8,7
Client satisfaction
Get in touch with our experts,
Want to know what we can do for your organisation?
Younes Seghrouchni
Managing Consultant GenAI & Data StrategyE-mail info@datasciencelab.nl
Carmen Wolvius
Managing Consultant Data Science & AIE-mail info@datasciencelab.nl
Stef Stoelwinder
Business DevelopmentE-mail info@datasciencelab.nl
Where we do that,
Latest blog posts,
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The organisations that do this,
Frequently asked questions,
AI can combine data from completed projects with the progress of ongoing work to flag risks earlier. This gives you a clearer view of which cost items are going off track, which suppliers are causing delays and where equipment could be put to better use.
Start with the question that comes up in every final cost review: where did this project go off track? Comparing estimates with actual costs from completed projects shows which items consistently deviate and where measuring during a project would pay off.
Cost estimates, schedules, purchase orders, time records, equipment management data and subcontractor records. They are often spread across different software packages and spreadsheets. The work lies in connecting these sources by project so they provide a single picture.
When there are enough completed projects to learn from, and decisions currently rely on experience: what price is viable in a tender, which equipment is needed on a given day, or which subcontractor poses a risk of delay. A model supports that judgement; the estimator and site manager make the decisions.
By showing the results in the project overview that planning and site teams already use, and agreeing who will maintain the model when prices, suppliers or working methods change. A report read only in the office changes nothing on site.