Look at sign-in success rate, average login time, recovery friction, and login-related ticket volume. If passkeys are deployed but the organisation still sees high failure rates, heavy support demand, or widespread fallback use, the implementation is incomplete or poorly governed. Adoption counts alone do not prove the programme is effective.
Why This Matters for Security Teams
Passkey performance is not a branding exercise. Security teams need evidence that authentication is reducing risk without creating hidden friction, because a deployment can look successful on paper while users quietly route around it with fallback methods, support workarounds, or recovery channels. Current guidance from NIST Cybersecurity Framework 2.0 emphasizes measuring outcomes, not just enabling controls, which maps well to passkeys: success rate, time to authenticate, and operational burden all matter.
NHIMG research on identity governance shows why adoption alone is an unreliable signal. In the Ultimate Guide to NHIs, only 5.7% of organisations report full visibility into their service accounts, a reminder that identity programmes often fail when teams track deployment counts instead of real control quality. The same mistake happens with passkeys when organisations celebrate rollout milestones but do not monitor recovery loops, fallback paths, or user friction. In practice, many security teams discover weak passkey governance only after help desk demand spikes or users start bypassing the intended login flow.
How It Works in Practice
Security teams should treat passkey health as an operational scorecard. Start with sign-in success rate, then break it down by device type, browser, app, location, and user population so you can see where failures cluster. Average login time matters because a secure method that is too slow will be abandoned. Recovery friction is equally important: if users repeatedly need reset links, device re-enrolment, or manual desk intervention, the programme is not stable.
Useful indicators usually include:
- Primary passkey success rate versus fallback password or OTP use.
- Median time to complete sign-in, not just first-time registration.
- Volume and category of login-related tickets.
- Recovery completion rate after lost-device or device-migration events.
- Share of users who can complete login without support.
Teams also need policy and assurance controls. NIST Cybersecurity Framework 2.0 is helpful here because it pushes organisations toward continuous monitoring and governance rather than one-time deployment checks. For identity-specific design, the Ultimate Guide to NHIs reinforces a broader lesson: identity controls only work when they are observable, rotated or refreshed where relevant, and tied to lifecycle management. Passkeys should be reviewed in the same way, with dashboards that expose fallback rates, exception handling, and enrolment health.
These controls tend to break down in BYOD-heavy environments with inconsistent device posture because the same user may authenticate cleanly on one endpoint and fail repeatedly on another.
Common Variations and Edge Cases
Tighter passkey governance often increases support and rollout overhead, so organisations need to balance better assurance against user recovery complexity. That tradeoff is real, especially during migration periods when users are moving from passwords, MFA apps, or legacy federation to phishing-resistant sign-in.
Best practice is evolving for edge cases. There is no universal standard yet for how much fallback is acceptable, but excessive fallback use is a warning sign. If a high-value workforce still depends on passwords for recovery or cross-device access, the deployment is only partially effective. The same is true if the passkey flow works well for managed laptops but fails on mobile devices, shared workstations, or contractor accounts.
Security teams should also watch for false confidence. A high enrolment rate can hide poor actual use, and a low ticket count can simply mean users have given up on the feature. Current guidance from NIST Cybersecurity Framework 2.0 supports measuring outcome quality, while the Ultimate Guide to NHIs underscores the broader governance lesson: identity controls must be measured in operational reality, not just in rollout statistics. The question is not whether passkeys exist, but whether they are the default path, consistently usable, and resilient under recovery pressure.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST CSF 2.0, NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | PR.AC-1 | Access control outcomes fit passkey success and fallback monitoring. |
| NIST CSF 2.0 | DE.CM-1 | Continuous monitoring is needed to spot passkey failures and drift. |
| NIST AI RMF | The govern function supports ownership and measurement of identity controls. |
Track authentication success and fallback use to verify access control is actually working.
