Kennisbank

When no one owns it in a multi-entity group

A group with multiple entities often has several versions of the same data point. One subsidiary measures scope 2 emissions via the energy supplier, another via a facilities company, a third supplies an estimate from a spreadsheet that no one can trace back to the source anymore. At group level this comes together in a single figure, but the question of who owns that figure often remains unanswered. Not because no one wants to pick it up, but because the group structure splinters ownership across entities that each have their own systems, definitions and people responsible.

Why this is typical for multi-entity groups

Within a single company, ownership is usually a matter of attaching a name to a task. In a group with multiple entities, the question first is: at what level does the ownership lie? Does responsibility for a data point rest with the entity that performs the underlying measurement, or with the group function that consolidates the figure? Both answers are defensible, and that is exactly the problem. Without an explicit choice, a grey area emerges in which the entity thinks the group is responsible for accuracy, and the group thinks the entity is responsible for the accuracy of the source measurement. What you understand by definition and scope here depends on who owns the definition of a data point at group level versus local level — a question that is separate from, but precedes, the question of who manages the process underneath it.

What goes wrong without an owner

When no one owns it, nothing visible happens right away. The figure simply comes in, from somewhere, and is included in the consolidation. The problem only shows itself when something has to change: a definition is tightened, an audit asks for substantiation, or this year's figure deviates sharply from last year's. Then it turns out that no one can explain where the number comes from, what assumptions are built into it, or who is authorized to approve an adjustment. For a single entity that is annoying. For a group with multiple entities it becomes a search across departments that all think someone else can answer the question.

This relates directly to who owns the process underneath a data point: not just who supplies the figure, but who is responsible for the steps that lead up to it — the measurement, the conversion, the entry into the system. In a group with multiple entities those steps can sit with different parties, and without a documented owner per step it is impossible to trace where a deviation arose.

Assigning ownership without forcing it

The solution is not to appoint an owner for every data point who happens to be available. That only relocates the problem. An owner must be someone who actually has influence over the source of the figure: the person who performs the measurement, manages the system, or checks the submission. For groups with multiple entities this often means a layered assignment — a local owner for the source measurement, and a group owner for the consolidation logic that combines the separate measurements into a single figure.

These two roles are not interchangeable. The local owner can confirm that the measurement at the entity is correct, but not that the aggregation at group level has been applied correctly, with the right conversion factors and without double counting. The group owner can manage the consolidation, but cannot guarantee that every underlying measurement is valid. Filling in both roles is necessary to know where a deviation originates when the audit at group level asks about it — a question that ultimately comes down to who owns the control on a data point: who signs off on accuracy, and on the basis of which underlying confirmations.

Documenting what often only exists verbally

In many multi-entity groups, ownership does exist, but only in the heads of people who have been in their position for years. Everyone roughly knows who does what, until that person is on leave, changes roles, or the question is just a bit more specific than the informal picture covers. A data point register that records, per data point, who manages the source, who does the consolidation and who signs off on accuracy, makes this independent of who happens to be reachable that particular week. That register does not need to be bigger than the group itself; it just needs to exist before the question becomes urgent.

The bridge to the work itself

Establishing ownership is one step; it is also a good moment to look at how much of the work that ends up with that owner actually requires judgment, and how much amounts to retyping figures from one system into another. The work scan from FTE TO AI calculates, per task, what portion of that work can be taken over by AI, so that an owner in a multi-entity group spends their time on the questions that genuinely require judgment, rather than on manually merging spreadsheets from different subsidiaries.