What is a qualitative extension of an IAM system, and what is the first question it raises?

A qualitative extension means the IAM is to process a new kind of information that lies outside its current scope; the first question is whether this scope extension is worthwhile at all.

Where a quantitative extension adds more of the same, a qualitative one adds something new: an attribute or information object the IAM has never handled, for example a driving-licence class, a security clearance or a professional certification. That changes the IAM itself:

• its data model needs new fields and rules,
• someone has to maintain the new data,
• a legal basis for processing it has to exist,
• a source for it has to be found or even built.

Because each of these costs effort and creates long-term obligations, the process puts a gate before all of them: "Is this IAM scope extension sensible?" (IAM-Scope-Erweiterung sinnvoll?). A "no" is a perfectly good outcome. It leads to a solution outside the IAM, typically inside the requesting application.

Go deeper:

• Data model (Wikipedia) — why adding a new kind of information means changing the model, not just loading more rows.