A figure in a sustainability report comes from somewhere. From an energy bill, an HR system, a spreadsheet someone set up three years ago that is now being filled in by a successor without that successor knowing why the formula is the way it is. As long as someone can answer that question, there is an owner. The moment no one can answer that question, there is a void. And a void in a data point is not a technical flaw that a tool fixes. It is an organizational fact that must first become visible before anything can be done about it.
Many organizations only discover that void at the moment an accountant, an auditor or a regulator asks a question that no one can answer. Who supplied this figure. Based on which source. Who checked whether that source is still correct. If the answer is "we no longer know", then there was never ownership. There was a spreadsheet that worked, until someone asked about it.
In a single-entity organization, the distance between a data point and the person managing it is usually small. There is one finance department, one controller, one person who compiles the scope 2 figures. As soon as a group consists of multiple entities, that changes. A subsidiary supplies data to a parent company. One division works with a different ERP system than another division. Everyone delivers what is asked, but no one has been given the task of monitoring whether the definition of a data point in one entity is the same as in another. That is a question addressed in more detail on the page about who determines the definition of a data point when a group consists of multiple entities.
That same pattern repeats itself at the level of the process. Who monitors that the steps between source system and reported figure are the same at every entity, and who intervenes if that is not the case. That, too, is rarely assigned explicitly; it grows along with the organizational structure, until a check is needed and it turns out no one oversees the process as a whole. How to properly assign that responsibility is worked out on the page about who manages the process behind a data point in a group with multiple entities.
A control is the step that checks whether a data point is correct, not the step that supplies the data point. That distinction seems subtle, but it is precisely where ownership often falls through. The person entering the figure feels responsible for entering it. No one feels responsible for checking it. In a group with multiple entities that difference is even greater, because the control often should sit at a different level than the delivery. Who makes that control someone's responsibility, and why that is a different question than who supplies the data, is described on the page about who owns the control on a data point in a group with multiple entities.
A specific variant of the void arises between two departments that both have a claim on a data point, but neither has full responsibility for it. Finance manages the systems where much of the underlying data comes from; sustainability manages the definitions and the reporting logic. Between those two positions fall data points that no one touches first. How that division can be made is addressed on the page about how to divide ownership between finance and sustainability.
If no one is the owner, usually nothing visible happens, until the moment something does happen. A figure is not updated because no one knew it had to be. A definition changes in one entity but not in another, and no one notices until the figures no longer add up. A spreadsheet is taken over by someone who does not know the logic, and the error that results goes unnoticed until an external party asks about it. These are not incidents that arise from carelessness. They arise from the absence of a name attached to a task.
Precisely for that reason, assigning ownership is not a side issue when setting up a reporting process, but the first step. Before a tool is purchased, before a dashboard is set up, the question "who owns this" is the question that determines whether everything afterward still holds up. A tool placed on top of empty ownership produces a neater report about the same unmanaged figures.
Once ownership has been clearly assigned, per data point, per process and per control, a second question arises: how much of the work that ends up with that owner is repetitive enough to hand off. Compiling a figure, checking a source, maintaining a register — part of that is manual work that keeps recurring. FTE TO AI calculates, per task, what portion of that work can be taken over by AI, so that the owner you have appointed does not get stuck in repetition but is left with the judgment that a human must make.
Vraag maar waar een datapunt vandaan komt. Dat is meestal de hele vraag.
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