The question seems simple, until you try to answer it. Sustainability data comes from HR systems, facility dashboards, energy suppliers, spreadsheets from individual employees and sometimes from the memory of someone who has been supplying the same figures for years. Without an overview, nobody knows exactly which data points exist, where they come from and whether they still match what was once recorded.
A data point register is the answer to that confusion. Not as a reporting tool, but as an administration of the data itself: what is a data point, where does it come from, who is responsible for it and which rules must it meet before it can be used.
A register is more than a list of names of figures. For each data point, at least the following should be recorded:
Without these fields, a list of data points is a collection of names without provenance. With these fields, it becomes visible where the data comes from and where the weak points are.
The order in which you build a register determines whether it yields anything. Do not start with the reporting structure, but with what is already recorded. Where does a data point already exist describes how to trace that: a figure often already exists in a different system than expected, under a different name or in a different unit.
Next comes the question of how you set up the structure itself, which fields are mandatory and in which order you add data points without the register becoming unmanageable. That process is described at how do you set up a data point register.
Not every data point immediately has an identifiable source. Some figures were once entered manually, taken over from an old report or estimated by someone who is no longer employed. What you do in that situation, and how you distinguish it from data points that do have a source, is described at what do you do with a data point without a source.
Another recurring problem is duplication: the same data point entering the register via two routes, with slightly different values. How you detect that before it leads to conflicting figures is described at how do you recognize a duplicate data point.
A data point being in the register does not mean it is correct. Being correct is a separate step: the value must align with the source definition, the unit must match what the quality rule expects, and the owner must be able to confirm that nothing has changed in the process since the last verification.
For that, it is necessary to know how the data point travels from source to report. Mapping that path is called source-to-report mapping, and it is a separate step alongside recording the definition. What that mapping precisely involves and why a register without that mapping remains incomplete, you can read at what is source-to-report mapping.
The question of when a register is complete enough to rely on has no fixed answer in numbers of data points. It depends on the scope of the reporting obligation, on how many data points already have a verified source and owner, and on how many are still marked as outstanding or unclear. A register is not finished because it looks complete, but because the outstanding points are known and managed. How you determine that is described at when is a register finished.
A data point register is a snapshot of what is currently recorded. Without maintenance, it degrades just as quickly as the spreadsheets it was meant to replace: sources change, owners leave, definitions shift without anyone updating the register.
Much of the work involved in keeping a register up to date is recognizable and repeatable: checking sources, testing values against quality rules, flagging changes. Which part of that maintenance can be supported with AI and which part still requires human oversight cannot be stated in general terms. The work scan from FTE TO AI calculates that per task, based on exactly what the task involves and how often it recurs, so that it becomes clear which part of the work can be taken over and which part cannot.
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.