Explains corrective and preventive action on a data nonconformity
Determine the cause, eliminate it at its level (data, process or design) so that the defect does not recur, add a control that detects a recurrence, and check whether the same cause acts elsewhere (ISO 9001:2015 clause 10.2; DMBOK2 ch. 13, 4.1-4.2).
Can AI do this?
AI does this well Most of the tested AI models master this. 4 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 98% | Mastered |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
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: Determine the cause, eliminate it at its level (data, process or design) so that the defect does not recur, add a control that detects a recurrence, and check whether the same cause acts elsewhere (ISO 9001:2015 clause 10.2; DMBOK2 ch. 13, 4.1-4.2).
How it is assessed: Answers a written question on the corrective action on a data nonconformity correctly
Related knobits
Needed for
- Q-501 Recognises a data fix applied at the symptom
- Q-505 Recognises a root cause fix with no control against recurrence
- Q-506 Recognises a root cause not looked for elsewhere
All 9 knobits of Analyse the root causes.
Source: Practice the stage 5 reference and review checklist rest on