Recognises a data quality goal with no business driver
A goal that names no driver it serves.
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 | 50% | Not shown |
| gemini-3.5-flash-lite | Low cost | 39% | Not shown |
| gpt-6-luna | Low cost | 50% | Not shown |
| claude-haiku-5-5 | Low cost | 50% | 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 driver the goal serves, or the goal dropped
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: QG-001 "99% data quality across all data", driver: null Acceptable: "FINREP F 18.00 inputs accurate to 99.9% by Q2 2027 (driver: supervisory finding on NPL data)"
Also known as: Goal with no business driver
Related knobits
Builds on
All 12 knobits of Set the data quality strategy and framework.
Source: Review checklist 00-dq-strategy, row 1 (DMBOK §2.2)