Compliance and Privacy Metrics, Monitoring and Reporting Questions

Approach / framework
Measure across Adoption, Reliability, Security Impact, and Operational Response. Use quantitative KPIs with sampling and dashboards feeding alerting thresholds.

Concrete KPIs

• Adoption rate = (users with MFA enrolled / eligible users) * 100
• Daily active MFA use = % of auths requiring MFA in last 24h
• Authentication failure rate = failed MFA attempts / total MFA attempts
• Bypass attempts = number of emergency bypasses or bypass-token usages
• Suspicious MFA resets = reset events initiated via helpdesk or self-service flagged by risk signals
• Account-compromise incidents = number of confirmed compromises per 1000 users (compare pre/post rollout)
• Phishing-resilience sample = % of phishing simulation victims who had MFA but were phished into resetting

Sampling approaches

• Full telemetry for enrollment and auths; stratified sampling for deep forensic review (high-risk users, privileged accounts, geolocation anomalies) at 5–10% baseline, 100% for privileged.

Dashboard design

• Top row: Adoption rate, daily active MFA, high-risk user adoption, trend 30/90d
• Middle: Failure rate heatmap by factor type (TOTP, push, SMS), top sources of failures
• Bottom: Incidents (compromises), bypass events, phishing-sim results, alerts
• Include filters: org unit, app, factor type, risk score.

Thresholds & remediation

• Adoption < 95% for privileged or < 80% org-wide → remediation campaign + block non-MFA access after 30 days
• MFA failure rate > 3% sustained over 7 days → investigate outages/config issues
• Bypass attempts > 1% of privileged logins or repeated bypass by same operator → immediate audit and suspend bypass capability
• Rise in compromises post-MFA rollout → emergency rollback/containment and root-cause forensic.

Why
These KPIs tie user behavior, system reliability, and security outcomes so decisions (user education, policy tightening, technical fixes) are data-driven.