At most organisations, there's a name under the sustainability report. A CSO, a controller, sometimes the CFO. That name is responsible for the end result: the figures that go out, the accompanying explanations. But the report is the tip of the iceberg. Beneath it lies a process of months: collecting data from systems and spreadsheets, applying definitions, having figures approved by people who know the source. Who owns that process is a different question from who signs the report, and that question often isn't asked.
The difference is not trivial. The owner of the report can be entirely honest and still be dependent on figures that no one manages structurally. If the process underneath has no owner, the report leans on the assumption that the right people do the right things at the right moment. That sometimes works for a year. It doesn't work structurally.
Ownership of the underlying process is something different from ultimate responsibility for the outcome. It means: someone knows for every data point where it comes from, who enters it, who checks it and what happens when the source changes. That is a role that can differ per data point. The energy data comes from facilities, the personnel data from HR, the supply chain information from procurement. Each of those sources needs a different owner, with different knowledge and different responsibility.
The question of who owns the control belongs directly with this. Control is not something that automatically arises the moment a reporting process has been set up. Someone has to manage the rules that determine whether a figure is correct, and that person is not automatically the same as whoever compiles or signs the report.
Without a designated owner, the work shifts to whoever happens to be available. A colleague who supplied the figure last year does it again this year, without anyone having recorded that this is her task. If she changes roles, the knowledge disappears with her. If the source methodology changes, no one notices until the report is already finished. What you do when no one is the owner describes this pattern: not as an exception, but as the default situation at many organisations that have only just started with structured sustainability data.
The costs of this void are not visible within a single reporting year. They become visible when someone leaves, when an audit asks questions no one can answer, or when two departments both assume the other has taken care of it.
Part of the ambiguity arises at the boundary between finance and sustainability. Both departments have a stake in the figures, both hold parts of the required data, and neither has by definition an overview of the whole. How you divide ownership between finance and sustainability is therefore not an organisational detail but one of the first decisions that has to be settled before a data structure becomes sustainable.
At organisations with multiple entities, this becomes a layer more complicated still. Who owns the definition of a data point when five subsidiaries each measure it slightly differently? Who owns the definition of a data point in a group with multiple entities and who owns the process beneath it in a group with multiple entities are questions that are not resolved by a reporting tool, but by agreements laid down before the system is set up. The control itself also shifts in complexity once there are multiple entities: who owns the control in a group with multiple entities is a different question than at a single organisation, and requires its own answer.
The temptation is great to leave these questions unanswered and purchase a tool that generates the report. But a tool placed on top of a process without owners produces neater reports about figures that no one checks structurally. The order is the reverse: first establish who owns which data point, who knows the source, who manages the quality rule. Only then does a tool have something to build on.
The Data Readiness Scan is built on that order. It is a data point register with lineage from source to report, with ownership and quality rules per data point. Not a reporting tool, not a questionnaire filler, but the register that records who is responsible for what, so that question no longer needs to be asked afresh every reporting cycle.
Once it's clear who owns which part of the process, a follow-up question arises: how much time does managing that ownership cost, and what part of it is work that by definition must be done by a human versus work that is repeatable and transferable. The work scan from FTE TO AI calculates per task which part of the work can be taken over by AI, and is a logical next step once ownership over the data has been established: only once it is known who owns what can it become visible which part of that ownership actually requires human work and which part can be structurally supported.
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.