What is a quantitative extension of an IAM system, and when is it necessary?
A quantitative extension is an extension of the same kind: the IAM can already process this type of information, but the currently connected data sources cannot supply it for the new need.
The key word is gleichartig, "of the same kind". Nothing about the IAM's understanding of the world changes: the data model already knows a person with a name, an organisation and an account. What is missing is more of the same, typically more people, coming from a source that is not connected yet.
Two conditions together define it:
- The IAM is capable of processing this kind of information (the attributes exist in its data model, the rules for them exist).
- The connected sources do not deliver it for the new need (for example the new people are not in any of them).
A quick test: if you could describe the change as "add another row-supplier to a table that already exists", it is quantitative. If you need a new column, it is qualitative.
Go deeper:
Master data management: Mergers and acquisitions (Wikipedia) — reconciling the same kind of master data when another company's systems arrive.