Top Compliance Metrics to Monitor and Improve 

Compliance metrics are how you turn ‘I think we’re fine’ into a defensible answer the next time your CEO or board asks questions like ‘Are we compliant today?’ or ‘Where are we exposed?’. 

Regulators now expect proof that your compliance program is effective, monitored, and improving, not just a policy binder on a shelf. However, in PwC’s 2025 Global Compliance Survey, only 7% of organizations rated themselves as ‘leading’ today. Yet 84% expect to be leading or mature within three years. How can we close this gap? Simply checking more boxes won’t do. You close it by instrumenting compliance with metrics that actually tell you how you are doing.

In this guide, we’ll move beyond generic KPI lists and show you how to design, operationalize, and automate metrics that align with real controls, risks, and business outcomes. We’ll also talk through how to scale those metrics across multiple frameworks without overburdening your team.

What are compliance metrics?

Compliance metrics are quantitative and qualitative measures that show how effectively your organization meets its regulatory, contractual, and internal policy obligations. They capture what happens in day‑to‑day operations, not just what’s written in your policies.

Think of them as the compliance instrumentation layer. 

1. At the program level, they might include:

• % of controls passing in the last 30 days
• Compliance health trend over the previous quarter
• Number and severity of open audit findings

2. At the control or process level, they get more granular:

• % of production accounts with MFA enabled
• Mean time to remediate critical vulnerabilities vs SLA
• Training completion rate for high‑risk roles

Compliance metrics tell you whether you’re compliant today, whether you’re improving or slipping over time, and where the gaps are, before an audit finds them.

Compliance Metrics vs KPIs vs KRIs

For clarity, separate these into three layers:

1. Compliance metrics

Any measure tied to a control, obligation, or process. For example, the number of privileged accounts or the count of overdue access reviews.

2. Compliance Key Performance Indicators (KPIs)

The subset of metrics you treat as success indicators for your compliance program. For example:

• ≥ 98% of in‑scope users have MFA enabled
• ≤ 5 open high‑severity findings at any point

3. Key Risk Indicators (KRIs)

Metrics that signal rising exposure. For example, repeated failure to patch critical vulnerabilities within SLA or a spike in exceptions to your access policy.

In mature standards, each recommendation may be designed to be assessed as a metric. It includes an assessment status (automated or manual), an audit procedure, remediation steps, and mapping to controls. 

In practice, that lets you turn guidance like ‘Ensure 2‑Step Verification is enforced for all users’ into a concrete metric such as Percentage of in‑scope accounts with MFA enabled. Compliance metrics are not abstract. They help you turn controls and obligations into measurable, reviewable facts.

Why compliance metrics are crucial for business

Compliance shapes growth, resilience, and stakeholder trust. It is much more than just ‘avoiding fines’. Better-coordinated compliance can deliver improved decision-making, transparency, and culture. Those outcomes depend on comparable metrics that enable leaders to see risk and performance across functions, rather than relying on anecdotes.

Let’s explore how these quantifiable insights transform compliance from a reactive necessity into a proactive strategic advantage.

1. Regulators expect proof of effectiveness, not just paperwork

Regulators and prosecutors increasingly ask whether your program is ‘well‑designed, adequately resourced, and working in practice’. Compliance metrics demonstrate that this is true, not just an assertion.

They let you demonstrate that:

• You don’t just have policies; you monitor adherence
• You don’t just access reviews; you close issues within defined SLAs
• You don’t just perform training, you reduce repeat non‑compliance

Compliance effectiveness and value are often hard to measure; that’s why many firms struggle to prove their program isn’t window dressing. Metrics make effectiveness visible, traceable, and auditable.

2. Complexity is exploding, and metrics are how you stay fast

The regulatory scope, internal policies, and your tech stack are all expanding simultaneously. You’re adding new products, new regions, and new vendors. Every one of those comes with fresh obligations and risks. Without hard metrics, your only view into that complexity is anecdotes from control owners, point‑in‑time audit-prep spreadsheets, and periodic status-check meetings.

That works until something breaks. It could be a new customer requirement, a failed control, or a surprise finding from an internal audit. Good compliance metrics fix that by:

• Turning control of health into numbers (coverage, failure rates, aging issues)
• Showing trend lines rather than snapshots (are we getting better or worse?)
• Making prioritization defensible (we fix this first because it reduces X risk fastest)

3. Metrics turn compliance from a cost center to a decision engine

Done well, compliance metrics become inputs to real decisions, not just report fodder. They help you:

• Prioritize investments, for example, where to automate next or where to add headcount
• Quantify trade‑offs, such as the cost of staying within your vulnerability SLA versus the risk of breaching it
• Inform product and GTM choices by showing which controls actually unblock deals or shrink customer security questionnaires

4. Good metrics prevent dashboard theater

Fragmented, easily gamed metrics undermine accountability, while standardized, tamper‑resistant metrics can serve as the basic building blocks for real oversight. 

Compare a dashboard that only displays training completion or policy uploads to one that shows control failure frequency, time-to-remediate, and risk trends. The latter gives leadership something they can act on. The difference is not the chart type; it’s whether the metrics accurately reflect reality or merely provide comfort.

5. Metrics make compliance more tangible 

When teams see their own metrics, such as access review completion, onboarding and offboarding hygiene, and exception rates, they get a concrete picture of what ‘good’ looks like. 

They can see how their daily behavior moves the needle, rather than compliance feeling like something that only happens during audit season.

Without metrics, compliance remains fragmented, reactive, and impossible to benchmark against obligations or peers. With them, you can balance value protection with value creation.

Categories of Compliance Metrics to Track

You don’t need 100 compliance metrics; you need a coherent set that covers the full lifecycle of your program: design, operation, detection, response, and learning. 

The categories below are the ones that mid-market CISOs and GRC leaders lean on most, along with example metrics in each.

1. Program health and control performance

Program health metrics provide your top-line view of compliance health. It is the one your board and auditors typically ask for first.

Example metrics:

• Overall compliance health score
• Percentage of in‑scope controls passing in the last 30/90 days
• Control pass rate by domain
• Policies, access, infrastructure, data protection, vendors, incidents, and so on
• Frequency of control failures
• Number of failing checks per week or month, broken down by severity.
• Age of failing controls
• Average and maximum days since a control first failed

Together, these metrics represent a 24/7 health indicator, powered by tasks, system checks, and reviews. If tasks transition from ‘due’ to ‘critical’ and then to ‘failing’, the health score will decrease, and the dashboard indicates exactly where the next audit will be most impactful.

2. Evidence and audit Readiness

Audit pain in the mid‑market is rarely about having no evidence. The real problem is not seeing what is missing until it is too late.

Example metrics:

• Percentage of required evidence items collected for the current audit cycle
• Percentage of evidence auto‑collected via integrations vs manually uploaded
• Percentage of evidence items reused across multiple frameworks or audits
• Number of findings per audit, percentage of repeat findings, and time to close findings

The evidence completion rate for automated versus manual items is a key metric because it provides a clear indication of both coverage and effort at a glance.

3. Access governance and identity hygiene

Identity and access are where many cloud-native mid-market organizations are most vulnerable. It is also where compliance metrics are easiest to define.

Here are some useful metrics to include:

• Number of privileged users and admins, including super‑admins, across key systems
• Percentage of accounts with MFA enabled, overall and for high‑value roles (admins, production access)
• Percentage of scheduled access reviews completed on time, per system
• Percentage of accounts inactive for more than X days or belonging to offboarded employees
• Risky sharing and app usage indicators, such as users with external file shares, users with less secure app access, or unusual app usage patterns

Admins should regularly review security and app usage reports. Those reports surface fields such as 2‑Step verification enrollment, external sharing, and use of less secure apps. Each of those fields can become a trackable access governance metric.

4. Training, policies, and culture

Frameworks such as ISO 27001, PCI DSS, and GDPR all require awareness and training; however, completion rates alone are insufficient. Better metrics consider both coverage and behavioral change.

Example metrics:

• Percentage of in‑scope employees who accepted required policies, by policy
• Training completion rate by audience (execs, engineers, support, vendors, etc.)
• Time to complete training: average days from assignment to completion
• Post‑training assessment scores: average scores, failure rate, and retake rate
• Percentage of incidents with root cause in training gaps (for example, phishing or mishandling data)

Sprinto surfaces policy acknowledgement and training completion as real numbers—e.g., 400 users in scope; 100 still haven’t acknowledged policies—which is far more helpful than a one‑time ‘training done’ checkmark.

5. Vulnerability, patch, and incident management

Vulnerability and incident metrics are where compliance metrics and SLAs begin to overlap with security operations.

Example metrics:

• Mean Time to Detect (MTTD) and Mean Time to Remediate (MTTR) for vulnerabilities and incidents, broken down by severity
• SLA adherence for critical vulnerabilities (e.g., percentage of essential vulnerabilities closed within 2 days)
• Open vulnerabilities by severity and age, exceptionally high/critical items older than your defined SLA
• Percentage of incidents handled within SLA

For instance, if your SOP states that critical vulnerabilities must be patched within 2 days, but they are taking 7 days, that gap is a compliance metric you must monitor and address.

6. Third‑party risk and vendor compliance

Regulators and customers increasingly expect evidence of supplier oversight, not just completed questionnaires.

Example metrics:

• Percentage of vendors discovered vs in use (SSO‑based discovery helps here)
• Percentage of critical vendors with completed assessments
• Average time to complete vendor due diligence, from onboarding to approval
• Number of KYC checks, transaction scans, and customer screening scans processed
• Percentage of vendors failing to meet required controls or SLAs

7. Regulatory and financial impact

Regulatory and financial impact metrics tie compliance back to dollars and risk, which is critical for CFOs and boards.

Example metrics:

• Cost of compliance vs. cost of non‑compliance: budget for compliance vs spend on fines, legal fees, and remediation.
• Cost per incident or per finding, including downtime, rework, and reasonable proxies for reputational impact.
• Audit prep hours per audit and number of external audit days per framework.
• Compliance‑linked revenue metrics, such as time‑to‑close deals requiring security reviews and win rate in security‑sensitive segments.

Responding to complexity with more people and more controls alone is not always sustainable. Organizations need compliance integrated into their technology and data stack to move faster while staying in control. Financial metrics are the key indicators that demonstrate the effectiveness of the shift.

8. AI and data governance (advanced)

If you are using AI in customer-facing or high-risk workflows, regulators and customers will soon expect AI-specific compliance metrics as well.

Some useful metrics to look at:

• Percentage of high‑risk AI use cases assessed for explainability and fairness
• Number of AI models with documented, auditable explanations
• Incidents or complaints linked to AI decision‑making
• Coverage of AI systems under an AI governance framework (for example, EU AI Act alignment)

Together, these categories provide a comprehensive view of compliance performance, encompassing control health and evidence coverage, training, incidents, vendors, and costs. Next, let’s make this real by mapping those metrics to specific frameworks and use cases, such as SOC 2, ISO 27001, PCI DSS, and HIPAA, so you know precisely what to track where.

Compliance metrics by use case and framework

Different frameworks focus on various outcomes, but you do not want to have separate dashboards for each. Design cross‑framework metrics anchored in your common control set and slice them by framework only when you need to. The sets below serve as starting points for typical mid-market environments.

SOC 2 (Trust Services Criteria)

SOC 2 focuses on demonstrating that you consistently operate controls across security, availability, confidentiality, processing integrity, and privacy.

Useful SOC 2 metrics:

• Percentage of SOC 2‑mapped controls passing in the last 90 days
• The percentage of production changes with approved tickets and peer review
• Percentage of production and admin accounts with MFA enabled, and percentage of offboarding actions completed within SLA
• Number of security incidents per period, and percentage handled within documented incident response SLAs
• Number and severity of SOC 2 exceptions expected in the following report

ISO 27001 (ISMS performance)

ISO 27001 expects you to plan, operate, monitor, and improve your ISMS. Metrics sit inside the standard’s performance evaluation clauses, so you need measures that match your ISMS objectives.

Useful ISO 27001 metrics:

• ISMS objective KPIs: For example, percentage of high‑risk assets with documented risk treatment plans 
• Percentage of risk treatment actions closed on time
• Percentage of the ISMS scope covered by internal audits each year
• Number of ISMS nonconformities and average time to resolve them

ISO does not prescribe exact metrics, but it does require measurable information security objectives. The metrics above turn those objectives into specific, trackable numbers.

PCI DSS (cardholder data protection)

Under PCI DSS, assessors focus on the implementation and monitoring of technical controls.

Useful PCI metrics:

• Number of unauthorized inbound rules and average time taken to remediate them
• Percentage of in‑scope systems with Anti-virus or Endpoint Detection and Response installed, updated, and reporting
• Percentage of scans completed on schedule and percentage of critical vulnerabilities fixed within the defined timeframe
• Percentage of in‑scope systems sending logs to a central SIEM and percentage of critical alerts investigated

HIPAA (healthcare privacy and security)

HIPAA compliance focuses on protecting PHI and proving that you operate appropriate safeguards.

Useful HIPAA metrics:

• Number of anomalous PHI access events investigated each month
• Percentage of business associates with executed BAAs and completed security assessments
• Time to detect, investigate, and notify (where required) for PHI incidents
• Percentage of the workforce with HIPAA‑specific training, broken down by role

GDPR and other privacy regulations

GDPR, CCPA, and similar laws expect you to demonstrate control over data subject rights, lawful processing, and minimization.

Useful privacy metrics:

• Number of Data Subject Access Requests (DSAR) received and percentage fulfilled within statutory timelines
• Percentage of in‑scope processing activities with documented legal bases and consents
• Percentage of systems with implemented retention policies and percentage of expired records purged on schedule
• Number of transfers under Standard Contractual Clauses or Binding Corporate Rules and percentage under active monitoring

Financial crime and sector‑specific use cases

In financial services, fintech, and other heavily regulated sectors, metrics often closely align with regulatory workloads.

Useful sector‑specific metrics:

• Number of KYC checks, customer screening scans, and transaction scans processed
• Percentage of alerts investigated within SLA and number of overdue alerts
• Number of Suspicious Transaction Reports (STR) and Suspicious Activity Reports (SAR) filed, and time from detection to filing

Cross‑framework common control metrics

The more frameworks you add, the more you need a common control framework that avoids duplicated effort. Instead of separate controls for each standard, define a single control, such as MFA, for all in-scope production accounts and map it to SOC 2, ISO 27001, PCI DSS, HIPAA, and other relevant standards. Then track a single metric, for example, the percentage of in‑scope accounts with MFA enabled. 

Modern GRC platforms, including Sprinto, use standard control mapping to test once and reuse results across multiple frameworks. That approach maintains consistency in metrics and prevents metric sprawl as new standards are introduced.

How to build a compliance metrics program

If you do not have a metrics program today, the goal is not to build a flawless dashboard on day one. The real goal is to answer sharper questions about compliance, then refine the numbers and visuals over time. Think of this as setting up automated data collection for your key controls, not decorating slides for auditors.

Let’s outline a practical sequence that aligns with how mature firms and AI governance research approach governance by metrics.

Step 1: Start with the questions, not the numbers

Before you pick metrics, write down the questions your leadership and auditors actually care about, for example:

• Are we compliant across our key frameworks today?
• If we had an audit tomorrow, where would we fail?
• Are we improving or degrading month over month?
• Where are we most exposed, and how quickly do we fix issues?

These questions serve as the anchor for your metric design and help you avoid collecting data simply because it is easy to pull.

Step 2: Define scope: frameworks, domains, and controls

Next, decide what is in scope for measurement:

• Frameworks such as SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR, and internal policies
• Domains such as access, infrastructure, data protection, vendor risk, training, and incidents
• Controls that must be continuously monitored

First, agree on the frameworks and controls that matter, then design KPIs around them, not the other way round.

Step 3: Map controls to measurable KPIs

For each critical control, ask two questions: what does ‘good’ look like, and how can we consistently measure that state?

For example, take a control such as ‘All production users must have MFA’. The corresponding KPI is the percentage of in‑scope users with MFA enabled, with a target of 100 percent and an alert if coverage drops below 98 percent. In the same way, for a control like ‘Critical vulnerabilities must be patched within two days’, you track both the percentage of critical vulnerabilities remediated within that window and the average days to remediate. You trigger an alert whenever that average moves above two days.

When you turn controls into measurable checks, define the expected state, how it’s assessed (automated/manual), how auditors should test it, and how owners should remediate failures.

Step 4: Design thresholds and scoring

Once you have KPIs, define how you will judge performance:

• Have thresholds, such as green at 98 percent or higher MFA coverage, amber at 95 to 97 percent, and red below 95 percent
• Scoring rules that describe how each metric rolls up into an overall health score or risk score

Define low, medium, and high performance bands for each metric and build dashboards that show successes and failures over time. Metrics that support audits and certifications must be transparent, reproducible, and governed by clear integrity standards.

Step 5: Instrument your data sources

Now work out where each metric will come from in practice:

• Identity providers such as SSO and IAM for MFA status, privileged access, and inactive accounts
• Cloud platforms such as AWS, GCP, and Azure for configuration and asset metrics
• Vulnerability scanners and ticketing systems for SLA and remediation metrics
• HRIS and LMS tools for training and policy metrics
• Vendor risk tools for third‑party metrics

You need to identify every system that can touch production and pull data from them, often via integrations, to support your KPIs.

Step 6: Assign ownership and governance

Metrics without owners tend to fade away quietly. Assign each metric or metric set to a clear control owner or domain owner, such as the infrastructure lead, HR lead, or vendor risk lead. Clarify how often they review their metrics and what happens when thresholds are breached, including escalation paths.

We recommend mapping each metric to a control owner and monitoring it at a defined cadence. Clear structures, defined risk actions, and dashboards will enhance the effectiveness and transparency of the oversight process.

Step 7: Build dashboards that drive action, not just reporting

You do not need a complete data warehouse on day one. You do need a clear, opinionated dashboard that helps people decide what to do next.

• Executive view with overall health scores, top risks, SLA breaches, and upcoming audits
• Domain views for access, training, infrastructure, vendors, and similar areas
• Trend lines that answer whether you are in a better place than last month, and where you are drifting

PwC finds that organizations with centralized compliance coordination achieve better decision-making, greater transparency, and faster execution, which is precisely what good dashboards should deliver.

Step 8: Close the loop and keep evolving

Finally, a metrics program only works if it feeds into real decisions and learning.

Utilize metrics to prioritize remediation work and automation efforts. Bake key metrics into OKRs, performance reviews, and incentives so they influence everyday behavior, not just audit season. Retire vanity metrics regularly and add new ones as risks, regulations, and technology change.

Compliance leaders should get a real seat at the strategic table. This aligns metrics with transformation goals and continually invests in technology and analytics to keep pace with change. The metrics roadmap from metric integrity, to private assurance and certification, to regulatory interoperability, is a useful mental model for maturing a compliance metrics program over time.

​​Tools that help monitor compliance metrics

Compliance metrics only work if they are fed by live data, not by last-minute spreadsheet updates every quarter.

Most mid-market teams perform best with a small, integrated stack that pulls data from the systems where work actually occurs. PwC’s study notes that “Compliance Pioneers” invest more in technology, data, and analytics than their peers, which is a polite way of saying that spreadsheets on their own are now a liability, not a strategy.

Think of your stack as four layers:

1. Cloud-native GRC and compliance automation platforms

This layer is your system of record for frameworks, controls, and evidence. It is where you define controls, map them to SOC 2, ISO 27001, or PCI DSS, and see those checks roll up into metrics such as the percentage of controls passing or the time to close failed checks.

What ‘good’ looks like here:

• Connects to cloud, code, identity, HR, ticketing, and vendor systems through integrations and APIs
• Maps multiple frameworks to a common control set so each evidence item serves more than one standard
• Continuously tests controls and auto-collects evidence instead of waiting for quarterly reviews
• Provides clear dashboards for control health, audit readiness, recurring failures, and SLA breaches

For your board, CISO, and auditors, this platform is usually the primary lens. Everything else in the stack should feed into it.

2. Security tooling that feeds metrics

A GRC platform is only as valuable as the signals it receives from your security stack. These tools generate raw events that serve as metrics for detection, response, and hardening.

Key sources include:

• Identity and access management (SSO, IAM) for MFA coverage, privileged access counts, orphaned accounts, and offboarding timeliness
• Vulnerability management and EDR for mean time to detect, mean time to remediate, patching SLA adherence, and backlog by severity
• SIEM and log management for log coverage, alert quality, and incident detection performance

When these tools are connected to your GRC layer, you move from ‘we patch quickly’ to ‘we patch 92 percent of critical vulnerabilities within 48 hours,’ and you can prove it.

3. People and vendor-focused systems

Most mid-market incidents still trace back to human error or third-party issues rather than exotic zero-day vulnerabilities. Your metrics need to reflect that reality.

Core systems to tap:

• HRIS and LMS for training completion, policy acknowledgement, and joiner-mover-leaver hygiene
• Vendor risk and procurement tools for assessment coverage, critical vendor status, and remediation follow-through

These feed power culture and governance metrics, such as the policy acknowledgement rate by department and the percentage of critical vendors with current assessments, which are precisely the kinds of numbers regulators expect to see.

4. BI and analytics layer for mature teams

Once the basics are automated, leadership will ask a different question: what do these metrics do for the business? A BI or analytics layer helps you answer that.

Typical uses:

• Blend compliance metrics with sales data to see how audit readiness affects deal velocity and win rates
• Combine outage, vulnerability, and incident data to estimate downtime avoided through better control performance
• Build executive scorecards that roll technical metrics into business-level risk indicators

You do not need this layer on day one, but it becomes essential once you are trying to show return on investment, not just pass audits.

Done well, this stack lets you answer executive questions in minutes instead of weeks of manual evidence chasing. Whatever tools you choose, judge them by how much manual work they remove and how clearly they show risk, not by how many dashboards they promise. 

How Sprinto helps monitor compliance metrics

Sprinto turns your compliance program into live, audit-ready compliance metrics, not static checklists. Sprinto AI maps checks, controls, policies, and risks so the numbers you see reflect what is really happening in your environment. CISOs receive a single health score, along with drill-downs by domain, framework, owner, and timeframe.

Sprinto’s health score combines passing checks, completed workflows, and on-time tasks into one view. When items fail, the score drops, and the dashboard highlights the exact controls and evidence that an auditor would question today.

Out of the box, Sprinto tracks domain metrics for access, training, vulnerabilities, incidents, vendors, and more. Because Sprinto connects directly to identity, cloud, HR, and ticketing systems, these metrics are updated continuously rather than once a quarter.

Sprinto AI agents watch for evidence gaps, policy drift, and framework changes. Infinite Framework Mapping keeps one common control set aligned with every framework you adopt. You can achieve consistent KPIs across SOC 2, ISO 27001, PCI DSS, HIPAA, and custom standards without needing to rebuild reports.

If you’d like to see what your compliance metrics could look like in Sprinto, book a working session with our team, and we’ll map it to your current frameworks and tech stack.

FAQs

1. What are compliance KPIs?

Compliance KPIs (Key Performance Indicators) are the small set of metrics you treat as success benchmarks for your compliance program, things like:

• Percentage of in‑scope users with MFA enabled
• Percentage of critical vulnerabilities fixed within SLA
• Percentage of evidence auto‑collected vs manual

They’re a subset of all compliance metrics, focused on what matters most to your posture and strategy.

2. What are key risk indicators (KRIs) in compliance?

Key Risk Indicators (KRIs) are metrics that signal rising exposure or drift, for example:

• Increase in high‑severity control failures over the last quarter
• Repeated breach of patching SLAs for critical systems
• Spike in vendor incidents or exceptions

They help you see where compliance gaps are most likely to translate into real risk.

3. How many compliance metrics should we track?

For most mid-market organizations, 10–20 program-level metrics (for executives and the board) and 5–10 domain-level metrics per critical area (access, infrastructure, training, vendors, and incidents) are typically sufficient. If your team can’t explain why a metric exists and what they’ll do when it changes, it’s probably noise.

4. Are compliance metrics mandatory under frameworks like SOC 2 or ISO 27001?

Most frameworks don’t say you must have metrics, but they implicitly require measurement:

• SOC 2 expects you to show operating effectiveness over time.
• ISO 27001 explicitly requires measurable information security objectives and regular performance evaluations.

While specific metrics aren’t mandated, having and using them is the most practical way to demonstrate that you’re meeting these expectations.

5. How do you measure compliance posture?

Compliance posture is typically measured as a combination of:

• Control health (pass/fail status, failure frequency, and age)
• Coverage (how much of your environment and frameworks are actually in scope and monitored)
• Responsiveness (how quickly you remediate failures and close findings)

Tools like Sprinto roll these into a single health score, along with supporting dashboards, so you can see posture at a glance and drill down when needed.