Construction organizes itself around projects, not around the business as a whole. Each project has its own team, its own subcontractor chain and often its own way of recording. Where a factory has a fixed production process with recurring measurements, a construction company has a series of temporary work arrangements that fall apart once completed. The data generated during a project often disappears along with the project: into an archive folder, onto the laptop of a project manager who has since moved to a different job, or nowhere at all.
That makes the relationship between the data that is generated and the portion of it that ends up centralized different than in sectors with a continuous process. The largest part of the relevant information — material consumption, transport movements, energy on the construction site, waste streams — is generated on location and by third parties, and only a small part of it is structurally recorded in a place where someone can find it again later.
Material consumption and the origin of construction materials are a core component of many sustainability reports, but the data on this is fragmented across supplier invoices, delivery notes and sometimes only verbal agreements with a subcontractor. A contractor orders concrete, steel and insulation material through various suppliers per project, and not every supplier provides the same level of detail about origin, CO2 intensity or recycling percentage. Anyone who wants to know how much CO2 burden is contained in a year's material use must first know which projects were running, which suppliers were involved in them, and which of them supply data that is usable.
A construction project often runs on a chain of subcontractors: earthworks, installation technology, finishing, electrical work. Each subcontractor has its own business operations, its own vehicles, its own fuel consumption and its own waste registration. For the main contractor this is often a black box: there is a contract and a completion date, but not necessarily insight into the environmental data generated by the subcontractor's work. This issue is not unique to construction. In the installation sector too, relevant data is spread across subcontractors and service companies, and the way ownership is assigned there is a useful reference point for construction.
On the construction site itself, data is generated that is rarely recorded systematically: fuel consumption of cranes and generators, water use, waste containers being removed. This kind of data is often on paper work orders, in the heads of site supervisors, or nowhere at all. Similar bottlenecks with physical, scattered registration occur in the transport sector, where trip data and fuel consumption per vehicle and driver are recorded. The similarity is that the data is generated on the floor or on the road, and does not automatically find its way to a central system.
Alongside the construction site itself runs an administrative layer: equipment rental companies, inspection bodies, energy suppliers for site cabins and offices. These parties supply invoices and reports that contain relevant information, but that information is not labeled as sustainability data and therefore has to be extracted. This resembles the situation in wholesale, where purchasing and logistics data runs through multiple systems without anyone recognizing it as environmental data. In both cases, the first step is not collecting new data, but recognizing existing data that is already lying somewhere.
It is tempting to purchase a software package that is supposed to centralize sustainability data for construction. But a system that produces reports on top of an unorganized collection of project folders, subcontractor contracts and loose work orders delivers neater reports about figures whose origin nobody can verify. Before a tool is useful, it must be established which data point comes from which project, who is responsible for it, and via which route that data point reaches the report. That is a registry issue, not a software issue.
For a construction company, this means that the first task is not the reporting itself, but mapping out where the data per project, per subcontractor and per location comes from, who owns it and which quality rules apply to it. That register does not yet exist as standard in the sector, and building it up differs per company, depending on the number of ongoing projects and the extent to which subcontractors already share data.
The Data Readiness Scan is under construction. Anyone who wants to help think through this issue for construction, or wants to get access first, can sign up for the waiting list.
Once it is clear which data is generated where and who is responsible for it, the question often follows as to which part of collecting and structuring it remains manual work and which part can be automated. FTE TO AI's work scan calculates, per task, what portion of the work can be taken over by AI, and in this way offers a follow-up step for anyone who, after organizing the data, wants to know where the deployment of people is still most needed.
Vraag maar waar een datapunt vandaan komt. Dat is meestal de hele vraag.
Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.