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About This Automation
Access reviews require IT teams to manually export user lists from multiple systems, consolidate data, and cross-reference against org charts to identify policy violations. This manual work is error-prone, time-consuming, and often incomplete.
Automation continuously monitors user access across all systems, detects policy violations automatically, and routes findings to managers for approval. Changes are executed immediately upon sign-off, reducing review cycles from weeks to days.
Key features:
Compare user access across identity providers and cloud applications against defined security policies
Identify violations including shared accounts, excessive permissions, and inactive users still active
Route findings to managers via messaging tools and track approval responses automatically
Execute access changes and role updates across all systems based on approvals
Generate complete audit reports with full change history and compliance documentation
The issues teams report most often with this process
#
Friction point
Companies Report This
1
Manual data consolidation
Exporting and combining user lists from multiple systems is time-consuming and introduces duplication errors.
80%
2
Cross-system reconciliation
Matching users across identity provider and cloud applications requires manual comparison and standardization.
67%
3
Manager approval delays
Tracking responses and following up on missing approvals extends the review cycle significantly.
53%
4
Incomplete violation detection
Manual sampling misses policy violations that comprehensive automated scanning would catch.
40%
5
Audit trail gaps
Manual processes lack complete documentation of who approved what and when changes were made.
26%
DisclaimerAll data is based on anonymized FullSpec mapping sessions and proprietary industry research. Learn more
Automation readiness
How well-suited this process is for automation
Process Pain Score™Manual consolidation and cross-referencing across multiple systems is.
9.1/ 10
AI Fit Rating™Policy comparison and violation detection are highly structured, rule-based.
8.9/ 10
Automation Lift Index™Automation reduces cycle time from weeks to days and improves detection.
8.6/ 10
Hidden Overhead™Context switching between systems and manual tracking of manager responses.
7.4/ 10
How The Automation Works
The full workflow, from trigger to completion.
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1. Access Review Cycle Triggeredtrigger
Scheduled review date arrives or a policy change is detected. The automation platform receives the trigger and begins the review workflow.
2. Fetch User Data
The automation queries API to retrieve the current user roster, roles, and last login timestamps. Data is stored in memory for processing.
3. Fetch User Data
The automation queries API to retrieve user accounts, group memberships, and status. Data is merged data.
4. Fetch User Data
The automation queries API to retrieve workspace members, roles, and last activity. Data is consolidated with the growing dataset.
5. The automation Analyzes Access and Detects Violations
The automation compares consolidated user data against policy rules (shared accounts, excessive permissions, inactive users, role mismatches) and flags violations with severity and context.
6. Notify Managers
The automation sends a structured message to each department manager listing users requiring access review or removal, with a link to approve or dispute findings.
7. Log Findings
All detected violations and manager approvals are logged as tickets, creating an audit trail and enabling IT to track remediation.
8. Generate and Archive Audit Report
The automation compiles a final audit report with all findings, approvals, and changes, stores it in a compliance-ready format, and marks the review cycle complete.
Everything you need to know before mapping this process.
Disputed findings are flagged and escalated to IT leadership for review. Changes are not executed until all findings receive approval or explicit rejection with documented reasoning.