If you ask who supplied the figure for scope 2 emissions, you usually get a name. If you ask who established what does and does not belong in that figure — which locations, which energy sources, which period, which conversion factor — things go quieter. The figure has a sender. The definition behind it often does not.
That distinction is not pedantic. A data point is more than a value in a cell. It is a value plus a set of choices: what counts, what does not count, according to which source, with which assumptions for missing data. Whoever enters the figure is not automatically the one who made those choices, and certainly not the one who should be able to change them.
Without a designated owner of the definition, a fixed pattern emerges. The person closest to the figure — often a controller or a sustainability employee under time pressure — makes the choice themselves, on the spot, without documenting it. Next year a different person sits in that seat, or the same person remembers it differently. The definition shifts without anyone having decided to shift it.
The damage only becomes visible upon comparison. This year's figure next to last year's, or the figure from one location next to another's, and the question arises: are these the same definitions? Often the answer is neither yes nor no — nobody knows, because no one saw answering that question as their task.
This is a different problem from who owns the process behind it. The process concerns the steps: who collects, who checks, who submits. The definition concerns the meaning of what flows through that process. You can have a watertight process around a data point that no one has unambiguously defined, and then something consistently flows through that is not consistent.
The definition of a data point falls between the usual roles. Finance generally owns the figures and the controls over them, which is a different question from who owns the control — control checks whether a value has been processed correctly, not whether the underlying definition is correct. Sustainability generally owns the substantive knowledge of what an indicator should measure, but not always the authority to establish a definition group-wide. Both parties can point to the other without either feeling responsible for the eventual documentation. How you actually divide this depends on where the factual knowledge sits and where the authority to decide lies — a division that differs per organization and is elaborated further on the page about the division of ownership between finance and sustainability.
In a group with multiple entities this gap widens rather than narrows. A parent company can establish a definition, but whether that definition is also applied that way at a subsidiary in another country, with a different accounting system and a different local interpretation of what 'personnel' or 'revenue' means, is a separate question. That specific complication is addressed on the page about who owns the definition of a data point within a group with multiple entities.
For some organizations, appointing an owner for a definition feels like an extra layer of administration on top of a process that is already burdensome enough. The opposite is true. Without that owner, every discussion about a deviating figure becomes a discussion without a referee — everyone has an opinion about what the data point should mean, no one has the final word.
An owner of the definition does not have to be the one who collects or enters the data. The role is narrow: this person or function establishes exactly what the data point encompasses, approves changes, and is the point of contact when two departments interpret a figure differently. Without that role, the question of what you do when no one is the owner remains unanswered until someone — an auditor, a regulator, an investor — asks the question at a moment when a quick answer no longer suffices.
The first step is not appointing a name to a job title, but making visible each data point and the choices hidden within it. Only once those choices are on paper is there something to attach ownership to. That is precisely where the Data Readiness Scan begins: a register per data point with the origin, the assumptions, and the place where those choices were made, so that ownership can be assigned to something concrete instead of to a vague responsibility.
Anyone wondering how much of the work involved in maintaining and updating those definitions can be done with the support of AI will find at FTE TO AI a work scan that calculates per task which part of it is transferable to AI — a separate question, one that only becomes relevant once the tasks and their owners have been documented.
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.