A team should revisit its model or vendor decision when current production evidence calls the original choice into question or when changed use-case requirements make the earlier evaluation incomplete. The reassessment should examine the measures relevant to the use case rather than rely on one headline score. Production performance should be reviewed from both data-science and operational perspectives.
When should the decision be reopened?
The cited guidance does not prescribe a fixed review interval. A team should nevertheless reopen the decision when:
- Production monitoring no longer supports the original choice against the team’s current acceptance criteria.
- Changed requirements introduce a task or condition that the original evaluation did not cover.
- A relevant measure—such as coherence, fluency, groundedness, relevance, or task completion—changes in a way that affects the decision.
- Safety or security needs change in a way the existing evaluation cannot assess.
- Data-science and operational monitoring reveal an unresolved gap or disagreement that could alter the comparison.
A change in one measure is a reason to investigate, not automatic proof that another model or vendor would perform better.
How to check whether the decision still holds
The team should begin with the original use case and documented decision criteria, then review the evidence relevant to each part of the system:
| Review area | Evidence to examine | Question for the team |
|---|---|---|
| Output quality | Coherence and fluency | Do observed outputs still satisfy the current quality criteria? |
| Retrieval, where relevant | Groundedness and relevance | Does retrieval-augmented generation remain appropriately grounded and relevant? |
| Task completion | Performance on the required task | Does measured completion still represent the work the use case requires? |
| Safety and security | Existing safety and security evaluation evidence | Do current conditions remain covered by the assessment? |
| Production performance | Data-science and operational monitoring | What does each perspective reveal, and do they require follow-up? |
The result of this check may confirm the existing decision. If it does, the team should record why the evidence remains sufficient. If important measures are missing, thresholds have been crossed under the team’s own criteria, or unresolved operational issues remain, a fresh comparison may be appropriate.
What the team must still confirm
The cited materials do not provide a universal review cadence, threshold, pass-or-fail rule, or rule that any metric decline requires changing providers. The team must therefore confirm:
- Who owns the decision and what events trigger a reassessment.
- Which measures matter for the current use case.
- What baseline, threshold, or comparison method applies to each measure.
- Whether production monitoring covers both data-science and operational perspectives.
- Whether the monitoring evidence is current enough to represent present production conditions.
- Any separate cost, contractual, legal, regulatory, certification, or data-handling requirements, which must be verified independently.