Real estate differs from most other sectors in that the data does not originate within the organization itself, but with a long line of others: tenants, managers, energy suppliers, installers and sometimes the previous owner of the building. Where a manufacturing company can still read its energy consumption from its own meter, a real estate owner is for the largest part of its CSRD data points dependent on third parties who actually use or manage the building. This makes the ratio between data the organization records itself and data that must come from elsewhere more skewed in real estate than in a sector with its own production processes.
Energy and water consumption per property form the core of the reporting, but the source differs greatly per building. For some buildings, consumption runs through a central meter that the manager reads, while for others each tenant has their own connection and the data must be requested per lease agreement. For older or smaller properties, smart metering is often completely absent and consumption is estimated based on floor area or comparable buildings. For the data point register, this means that for each property it must be recorded not only which value was used, but also whether that value was measured, requested or estimated, and who is responsible for it.
Energy labels, valuation reports and building technical inspections are usually prepared by external parties and delivered at arbitrary moments, not linked to the reporting cycle. These documents often contain exactly the data points needed for CSRD — energy performance, insulation values, installation type — but are scattered across emails, valuer portals and local folders at the asset manager. Without a fixed place where these sources are linked to a property and a reporting year, each reporting cycle involves searching anew for the most recent label or the latest valuation.
A significant part of the climate impact of a real estate portfolio lies in usage by tenants, not in management by the owner itself. These tenants are rarely obliged to share data and often have no interest in providing it. This touches on a question that is not unique to real estate: which data point does the organization actually need, and from whom can it reasonably be expected to be delivered. In case of doubt about the scope of requested data, it is useful to look at how organizations with multiple locations or units determine which data points are actually relevant, because the same consideration applies to a portfolio with many properties and tenants.
Many real estate owners leave day-to-day management to an external party that manages invoices, consumption data and maintenance records in its own system. This intermediary link means the owner often cannot access the source data directly, but is dependent on exports, reports or manual transfer by the manager. When a manager changes or a contract ends, access to historical data regularly disappears as well, which makes the lineage of a data point — from original measurement to figure in the report — additionally vulnerable.
Dependency on external parties for crucial data is not unique to real estate. Those who want to see how a sector with many subcontractors and changing locations views the same problem will find points of reference in how the construction sector deals with data that originates with subcontractors and suppliers, and the way in which installation companies record consumption and material data that originates with customers and projects also overlaps with the position of a real estate manager between owner and tenant.
Within a larger real estate organization with multiple funds or business units, the same data point — for example the energy label of a building type or the CO2 factor of an energy supplier — often already exists elsewhere in the organization. Before figuring out again where a figure should come from, it is worth checking whether that data point has already been recorded at another business unit or another fund within the same organization. This prevents the same question being asked to a supplier or valuer multiple times, with the risk of differing answers.
The temptation is great to first purchase a software system that collects building consumption data and produces dashboards. But a system that pulls data from sources that no one has checked for ownership and reliability delivers a neater-looking report about figures that are still incorrect. First mapping out which data point comes from which party, who is responsible for it and which quality rules apply, is the step that precedes every system.
Once it is clear which data points come from where and who manages them, a second question naturally arises: which part of the work of collecting, checking and updating that data can be supported with AI. FTE TO AI has developed a work scan for this purpose that calculates, per task, which part of the work can be taken over by AI, so that it becomes clear where automation realistically contributes and where human oversight remains necessary.
The Data Readiness Scan for real estate portfolios is under development. Those who want the data point register, the lineage per property and the ownership of sustainability data to already be incorporated during its development can sign up for the waiting list. Nothing is being delivered yet; those who sign up will be informed as soon as the scan becomes available.
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.