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Governance, Ownership & Risk

How do organisations know whether secure access management is actually working in manufacturing?

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By NHI Mgmt Group Editorial Team Updated June 25, 2026 Domain: Governance, Ownership & Risk

They should look for fewer password resets, shorter time to access critical applications, reduced use of shared credentials, and fewer unplanned access exceptions. If workers still bypass controls to keep production moving, the access model is not working as designed.

Why This Matters for Security Teams

Manufacturing access management is only effective if it supports production without creating shadow access paths. Security teams often measure success by policy coverage, but the more useful signal is operational: fewer password resets, faster access to critical applications, fewer shared accounts, and fewer emergency exceptions. When those metrics improve together, controls are actually reducing friction instead of shifting risk elsewhere. That matters because plant-floor work rarely tolerates delays, and teams will bypass controls if the process is slower than the production deadline. The access model should therefore be judged against uptime, not just compliance.

NHI Management Group’s Ultimate Guide to NHIs notes that 97% of NHIs carry excessive privileges, which is a useful reminder that access problems are often hidden in routine operations rather than obvious incidents. For governance and measurement context, the NIST Cybersecurity Framework 2.0 is a practical reference point for aligning identity controls to business outcomes. In practice, many security teams discover their access model is failing only after workers start using shared credentials to keep the line moving.

How It Works in Practice

To know whether secure access management is working, organisations need to measure both security outcomes and production usability. In manufacturing, that means tracking whether access is granted with the right speed, to the right person or machine, with the right scope, and without creating workarounds. The strongest programs combine identity lifecycle controls, privileged access management, and NHI governance so that human workers, service accounts, and machine identities are treated as part of one operating model.

A practical measurement set usually includes:

  • Mean time to access critical applications, segmented by shift, site, and role.
  • Number of password resets and help desk tickets tied to access friction.
  • Frequency of shared credential use, especially on shop-floor terminals and automation platforms.
  • Count of unplanned access exceptions, including temporary admin grants.
  • Rate of access revocation after job changes, contractor offboarding, or line stoppages.

For non-human access, the bar is stricter. NHI Management Group’s Lifecycle Processes for Managing NHIs emphasises that credentials, rotation, and offboarding must be measurable, not assumed. That lines up with the OWASP Non-Human Identity Top 10, which highlights the operational risk of overprivileged and poorly governed machine identities. A healthy program should show fewer standing exceptions over time, faster recovery from access failures, and less dependence on tribal knowledge to get work done. These controls tend to break down in plants with legacy OT systems, vendor-managed tooling, and emergency maintenance workflows because access paths are often embedded in equipment-specific processes that cannot be changed quickly.

Common Variations and Edge Cases

Tighter access control often increases operational overhead, so organisations must balance speed against assurance. That tradeoff is especially visible in manufacturing environments where uptime is critical and downtime is expensive. Best practice is evolving, and there is no universal standard for how much access friction is acceptable across all plants.

Edge cases deserve special attention. Shared workstations, contractor access, and machine-to-machine integrations can make a control appear successful on paper while staff quietly bypass it in practice. A low password-reset rate is not a success signal if it simply means users are relying on cached sessions or shared accounts. Likewise, fewer exceptions can be misleading if teams stop requesting access and begin using informal routes instead.

For this reason, organisations should interpret metrics as a set, not individually. Pair access speed with exception volume, revocation timeliness, and evidence of credential sharing. NHI Management Group’s Regulatory and Audit Perspectives is useful when teams need proof that controls are operating continuously, not just at audit time. The measurement model should also reflect guidance from 52 NHI Breaches Analysis, which shows how overlooked identities can become the path of least resistance. In practice, the model fails when plants optimise only for login success and ignore whether access is being used in a secure, attributable, and revocable way.

Standards & Framework Alignment

This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.

OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.

FrameworkControl / ReferenceRelevance
OWASP Non-Human Identity Top 10NHI-01Measures whether shared and excessive NHI access is being reduced.
NIST CSF 2.0PR.AA-03Identity proofing and access success are core indicators of effective access management.
NIST CSF 2.0PR.AC-4Least-privilege enforcement should reduce exceptions and shared access workarounds.

Measure access latency, exceptions, and revocation timeliness as operational evidence of identity control effectiveness.

NHIMG Editorial Note
Reviewed and updated by the NHIMG editorial team on June 25, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org