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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.
NHIMG editorial — based on content published by Soffid: Identity Analytics: data management and analysis applied to access control
By the numbers:
- The module offers more than 30 types of visualizations to turn data into decisions.
Questions worth separating out
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 does identity analytics matter for NHI and privileged access governance?
A: Identity analytics matters because the same environment often contains humans, privileged accounts, third parties, and automated systems.
Q: What do security teams get wrong about authentication dashboards?
A: They often collapse success rate, fraud reduction, and user experience into one scorecard.
Practitioner guidance
- Map identity data sources before building dashboards Inventory which IAM, PAM, IGA, and application sources feed identity analytics, then document latency, completeness, and owner accountability for each source.
- Create separate behavioural baselines by actor type Treat employees, privileged accounts, third parties, and automated systems as different identity populations so anomalies are judged against the right normal.
- Align dashboard outputs to audit evidence needs Define which reports support access reviews, compliance checks, risk review, and incident triage before the next audit cycle.
What's in the full article
Soffid's full article covers the operational detail this post intentionally leaves for the source:
- The specific Identity Analytics capabilities across KPI, Access, Audit, and Risk dashboards for implementation planning
- The module’s report-generation and drill-down functions that matter when you need audit evidence quickly
- How identity data replication and integration support operational use across other applications and teams
- The way Soffid positions Identity Analytics alongside AM, IGA, and PAM in its platform
👉 Read Soffid's article on identity analytics for access control →
Identity analytics for access control: what IAM teams need now?
Explore further
12/07/2026 12:39 pm
Identity analytics is becoming the missing control layer between IAM data and IAM decisions. Many organisations can collect access events, but collection alone does not create governance. The operational value appears when identity data is normalized, filtered, and made actionable for security and audit teams. That is why identity analytics belongs in the same conversation as IGA, PAM, and ITDR. Practitioners should treat it as the layer that converts evidence into control action.
A few things that frame the scale:
- Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs.
- 79% of organisations have experienced secrets leaks, and 77% of those incidents resulted in tangible damage.
A question worth separating out:
Q: How can organisations tell whether identity governance is actually reducing risk?
A: Look for faster revocation, fewer orphaned identities, higher-quality ownership data, and review decisions grounded in usage evidence rather than static lists. If access issues are still discovered late or remain unresolved after reviews, the programme is generating compliance artefacts but not governance outcomes.
👉 Read our full editorial: Identity analytics exposes where access control lacks visibility
