Recognises a data quality framework with no route to improvement
No route from a result to a changed process.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 44% | Not shown |
| gemini-3.5-flash-lite | Low cost | 22% | Not shown |
| gpt-6-luna | Low cost | 22% | Not shown |
| claude-haiku-5-5 | Low cost | 22% | Not shown |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: The loop from measurement through analysis, issues and service levels to a changed process
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: Framework lists dimensions and a monthly dashboard only Acceptable: Measure, analyse (RCA), track (issues), control (SLAs), improve processes
Also known as: Framework that measures but does not improve
Related knobits
Builds on
- Q-052 Explains the ISO 8000-61 data quality management process reference model
- Q-053 Explains the data quality improvement cycle
All 12 knobits of Set the data quality strategy and framework.
Source: Review checklist 00-dq-strategy, row 4 (8000-61 (improvement process))