How should manufacturers use access analytics to reduce login delays?

Start by measuring where authentication takes longest, which devices fail most often, and which shifts show the highest retry rates. Then compare those patterns with workflow demand, device placement, and role design. The goal is to remove friction from the busiest paths first, not to optimise every login equally.

Why This Matters for Security Teams

Access analytics is often treated as a reporting exercise, but in manufacturing it is an operational control. When logins stall on shop-floor endpoints, shared terminals, kiosk stations, or remote maintenance access, the delay becomes a production issue as much as a security issue. The right analytics show where authentication friction concentrates, which roles are over-scoped, and where device posture or network placement is forcing repeated retries. That matters because identity problems compound quickly in environments with shift work and high device turnover, especially where NHI patterns overlap with automation and service access. NHI Mgmt Group notes that only 5.7% of organisations have full visibility into their service accounts in its Ultimate Guide to NHIs, which is a useful reminder that delay and visibility problems often share the same root causes.

Security teams get this wrong when they optimise for average login time instead of the highest-friction business paths. In practice, many security teams encounter repeated authentication failures only after operators have already started bypassing controls to keep production moving.

How It Works in Practice

effective access analytics starts by grouping login events by identity type, device type, location, shift, and application. That lets manufacturers distinguish between a genuinely slow authentication service and a workflow design problem such as MFA prompts on shared terminals, poor network paths on the plant floor, or access policies that do not reflect how work is actually done. The goal is to identify the small number of paths that create most of the delay.

From there, teams can tune access based on evidence rather than assumptions. For example, if a maintenance team repeatedly fails on badge plus password authentication at shift start, the issue may be poor device placement or a policy that is too rigid for time-sensitive work. If a specific line or site shows high retry rates, the root cause may be stale credentials, overlong session reauthentication, or a mismatch between role design and actual task frequency. Current guidance in OWASP Non-Human Identity Top 10 supports treating identity telemetry as a way to find excessive friction and excessive privilege at the same time.

Useful actions typically include:

• Comparing median and tail latency, not just average login time.
• Separating human operator access from service and machine access patterns.
• Flagging repeated retries by shift, site, device class, and application.
• Reviewing whether MFA, session timeout, or reauthentication timing is aligned to plant workflow.
• Reducing unnecessary step-ups for low-risk, high-frequency paths while keeping stronger checks on sensitive systems.

Where access analytics is especially valuable is in linking identity events to business context. NHI Mgmt Group’s Ultimate Guide to NHIs – Key Challenges and Risks is a practical reference point for understanding how weak visibility and excessive access widen operational risk. These controls tend to break down when manufacturers rely on legacy shared accounts across mixed OT and IT environments because the analytics cannot reliably attribute failures to a single user, device, or workflow.

Common Variations and Edge Cases

Tighter login controls often increase security assurance but also increase operator friction, requiring organisations to balance reduced risk against production continuity. That tradeoff is most visible in plants with shared workstations, intermittent connectivity, or heavily regulated access to safety-critical systems. Current guidance suggests that one-size-fits-all authentication policies are rarely appropriate, but there is no universal standard for this yet.

One common edge case is remote vendor support. These sessions often need stronger controls than internal operator logins, yet they can also create disproportionate delay if every access attempt is treated the same. Another is temporary labour or seasonal staffing, where access patterns change quickly and static role design becomes stale before the review cycle completes. In those environments, access analytics should be used to identify when temporary exceptions are turning into permanent workarounds.

Manufacturers should also be cautious about interpreting low delay as low risk. A fast login can still be over-permissive, especially if a shared account or cached credential is masking poor governance. The most useful metric is not simply speed, but whether the access path is fast for the right people and slow for the wrong ones. That framing aligns with the broader identity visibility concerns documented in the 52 NHI Breaches Analysis. In practice, the hardest cases are brownfield plants where legacy access, vendor tools, and modern IAM controls all overlap on the same production path.

Related resources from NHI Mgmt Group

• How should organisations reduce password reset volume without weakening access control?
• Why do ephemeral credentials still leave risk in machine access models?
• How should security teams use data classification to reduce access risk?
• Should teams use JIT access to reduce the impact of leaked passwords?