Topic starter
12/07/2026 12:15 pm
TL;DR: Identity analytics turns IAM operational data into dashboards, real-time monitoring, and audit-ready reporting so teams can see who is accessing what, spot anomalies, and support compliance more quickly, according to Soffid. The larger issue is not data volume but the governance gap between logging identity events and actually using them to control access.
Editorial analysis by NHI Mgmt Group, based on content published by Soffid: “Identity Analytics: data management and analysis applied to access control”.
Key questions
Q: How should security teams use identity analytics to improve access governance?
A: Security teams should use identity analytics to turn IAM data into decisions, not just reports.
Q: Why do server access controls fail when teams cannot see how sessions are being used?
A: Server access controls fail when visibility stops at authentication and does not extend into session behaviour.
Q: What are the signs that identity governance is not working in practice?
A: Common warning signs are repeated access workarounds, ignored approval workflows, super admins holding too much power, and teams bypassing the process because it is too slow or hard to use.
Practitioner guidance
- Define access visibility requirements by identity type Separate employee, privileged, third-party, automated-system, and bot reporting so each population is reviewed against the right control expectations.
- Build dashboards around control decisions Use dashboards to show who has access, which access paths are unusual, and which items need review rather than producing reporting for its own sake.
- Link behavioural signals to review workflows Route anomalous access patterns into recertification, PAM review, or incident triage so analysis leads to a documented decision.
Bottom line: Identity analytics addresses a common IAM weakness: organisations may have the data they need but still lack the visibility required to control access confidently.
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12/07/2026 12:39 pm
Identity analytics closes the visibility gap between logging and governance. Many IAM programmes collect events but still cannot answer the control question that matters most: who has access, what are they doing, and does it match what the organisation intended? That gap shows up in audits, in access reviews, and in day-to-day operations. The practical conclusion is that visibility becomes a governance capability only when it is tied to decision-making.
A few things that frame the scale:
- 69% of security leaders agree identity management must fundamentally shift to address agentic AI systems, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What is the difference between identity analytics and traditional access reporting?
A: Traditional access reporting shows static snapshots of entitlements, while identity analytics connects data across systems to reveal patterns, trends, and risk signals. It can show how access evolves over time, where privilege growth is occurring, and where SoD conflicts may exist. That gives governance teams a more decision-ready view than simple lists of accounts and roles.
👉 Read our full editorial: Identity analytics exposes where access control lacks visibility