SOC Metrics and KPIs That Matters in 2026

TL;DR

Most SOC teams track too many metrics and miss the ones that matter. Focus on metrics that show how fast you detect threats (MTTD), how quickly you fix them (MTTR), and whether your alerts are worth investigating. Skip the vanity numbers. Track what reduces actual risk to your business.

Key Takeaways

• MTTD and MTTR are your north star metrics—they show how fast you catch and stop threats
• Alert quality matters more than quantity; false positive rates reveal whether your SOC is drowning in noise or focused on real threats.
• Incident response metrics reveal whether your SOC operates reactively (firefighting) or proactively (threat hunting).
• Automation coverage shows how much manual work you've eliminated—and how much analyst time you've freed for high-value investigations.
• Ensure that you monitor the risk related metrics and not just the tickets alone.

Introduction

In a Quora confession, a SOC analyst revealed: "We're measured on how many alerts we close, not how much risk we reduce." This is a common issue with security metrics. Many teams follow statistics that appear good in charts but which do not serve to increase the safety of the organization itself. 

According to the 2024 Cost of Data Breach Report by Ponemon Institute, companies that extensively deployed AI and automation in security saved $1.76 million compared to those without it, but this was dependent on whether they monitored appropriate data points.

What Are SOC Metrics and KPIs?

SOC metrics measure how well your Security Operations Center detects, responds to, and prevents threats. KPIs (Key Performance Indicators) are the specific metrics that matter most to your security goals.

Common SOC Metrics

• Mean Time to Detect (MTTD)
• Mean Time to Respond (MTTR)
• Mean Time to Contain (MTTC)
• False Positive Rate
• True Positive Rate
• Alert Volume
• Incident Response Time
• Threat Detection Coverage
• Analyst Workload
• Automation Rate
• SLA Compliance
• Containment Success Rate

Common Security KPIs

• Number of detected incidents
• Critical vulnerabilities patched within SLA
• Percentage of alerts triaged automatically
• Escalation rate to senior analysts
• Audit readiness score
• Risk reduction percentage

Why Do Security Metrics and KPIs Matter?

You can't fix what you don't measure. SOC metrics show you where threats slip through, where your team wastes time, and whether your tools actually work.

They help you:

• Leadership must be convinced of the ROI: A 45% reduction in MTTR through automation demonstrates clear ROI and can justify investment in tools and potentially additional specialized staff for strategic work.
• Prevent breaches by identifying early signs of a problem: If there is a sudden increase in false alarms, then it shows that your identification rules are not efficient enough. When you have extended mean time to detect (MTTD), it implies that intruders stay for too long within your network.
• Become more intelligent in decision making: Do metrics indicate hiring additional analysts, purchasing new tools or automating routine tasks?
• Compare with what is observed in the industry: The mean time to detection for the year 2023 globally was estimated at 204 days as per IBM Security X-Force Threat Intelligence Index 2024. Behind schedule if your figure is higher than this.
• Stop alert fatigue: When 90% of alerts are false positives, analysts burn out. Tracking false positive rates forces you to fix noisy detections.

A Gartner report found that SOC teams spending less than 30% of their time on actual threat hunting are essentially firefighting all day. Metrics reveal whether you're hunting threats or just clearing queues.

What Are Some Common SOC Metrics?

Here's what each metric means, how to measure it, and why it matters.

Mean Time to Detect (MTTD)

What it is: The average time between when a threat enters your environment and when your SOC detects it.

How to measure it: Subtract the attack start time from detection time. Track this across all incidents and calculate the average.

Why it matters: Attackers move fast. Every minute they go undetected increases damage. Lower MTTD means you catch threats before they spread. According to Mandiant's M-Trends 2024 Report, the median dwell time for attacks detected internally was 16 days in 2023. External detection cut that to 9 days.

Target benchmark: Under 24 hours for most organizations. High-risk industries should aim for under 1 hour.

Mean Time to Respond (MTTR)

What it is: The average period taken to go from detection to containment or resolution of a threat.

How to measure it: Measure the timeline starting from when the alert was made until the incident is closed, then divide that into manageable parts like confirmation, analysis, prevention and cure.

Why it matters: Spotting a threat quickly means little if the response drags on for hours or days. MTTR reflects whether teams have clear playbooks, the right tools, and the authority to act fast. Organizations implementing automated response workflows can achieve 45–55% faster MTTR..

Target benchmark: Less than one hour for critical incidents. Less than 24 hours for high-priority alerts.

Mean Time to Contain (MTTC)

What it is: The time required to stop a threat from spreading once it has been detected.

How to measure it: Track the window from when containment begins to when the threat is fully isolated—such as blocking an IP, quarantining a device, or disabling a compromised account.

Why it matters: Containment is about damage control. If isolating a compromised endpoint takes days, malware or ransomware can move laterally and escalate the impact.

Target benchmark: Under 30 minutes for automated containment. Under 4 hours for manual containment.

False Positive Rate

What it is: The percentage of alerts that prove to be benign after investigation.

How to measure it: Divide the number of false positives by total alerts and multiply by 100.

Why it matters: Excessive false positives exhaust analysts and bury real threats in noise. When 90% of alerts are meaningless, teams start tuning out—and that’s when real attacks slip through. Research indicates that organizations with false positive rates above 55% experience higher breach rates, as alert fatigue causes analysts to miss genuine threats buried in noise.

Target benchmark: Under 20% for mature SOCs. Under 10% is world-class.

True Positive Rate

What it is: The percentage of real threats your SOC successfully detects.

How to measure it: Divide confirmed incidents by total actual threats (including ones you missed). This requires red team exercises or third-party assessments to know what you're missing.

Why it matters: This shows detection accuracy. A 60% true positive rate means 40% of real attacks slip past your defenses.

Target benchmark: Above 80% for mature SOCs. Above 90% is excellent.

Alert Volume vs. Actionable Incidents

What it is: A comparison between the number of all alerts and those that lead to action.

How to measure it: Monitor total daily generated alerts against those that are escalated for further review..

Why it matters: Volume doesn't equal value. A SOC generating 10,000 alerts per day with only 50 actionable incidents has a 0.5% signal-to-noise ratio—meaning analysts waste 99.5% of their time on false positives. This is the definition of alert fatigue. This metric reveals whether your tools generate noise or signal.

Target benchmark: At least 30% of alerts should be actionable. Mature SOCs aim for 50%+.

Analyst Workload and Efficiency

What it is: The number of alerts each analyst handles daily and how long investigations take.

How to measure it: Track alerts assigned per analyst and average time per investigation.

Why it matters: Overloaded analysts make mistakes and burn out. According to ESG Research, 70% of SOC analysts report being overwhelmed by alert volume, contributing to an industry-wide burnout crisis where the average analyst tenure is under 2 years. High workload correlates with higher turnover and missed threats.

Target benchmark: Under 50 alerts per analyst per day. Average investigation time under 15 minutes for routine alerts.

Automation Rate

What it is: The share of alerts or SOC tasks that are handled automatically, without needing an analyst to step in.

How to measure it: Compare the number of automated actions to the total volume of SOC tasks.

Why it matters: Automation gives analysts their time back. Repetitive actions—like blocking known-malicious IPs or disabling compromised accounts—should run on their own, not wait in a queue.

Target benchmark: Automate 50–70% of repetitive tasks.

SLA Adherence

What it is: The percentage of security incidents resolved within the timeframes defined by your service level agreements (SLAs).

How to measure it: Track how many incidents are closed within SLA timelines versus the total number of incidents.

Why it matters: SLAs connect security operations to real business commitments. Missing them can lead to compliance issues, unhappy customers, or even contractual penalties.

Target benchmark: Maintain SLA compliance above 90%.

Incident Escalation Rate

What it is: The portion of alerts that need to be escalated from Tier 1 analysts to Tier 2 or Tier 3.

How to measure it: Divide the number of escalated alerts by the total alerts initially handled by Tier 1.

Why it matters: A high escalation rate (>15%) often signals inadequate Tier 1 training, poor alert enrichment, or overly complex detection rules. A lower rate indicates Tier 1 analysts have sufficient context, effective playbooks, and the authority to resolve common incidents without escalation.

Target benchmark: Keep escalation rates under 15%.

Attack Mapping Coverage

What it is: The percentage of incidents mapped to MITRE ATT&CK tactics and techniques.

How to measure it: Track incidents with ATT&CK tagging vs. total incidents.

Why it matters: Mapping helps you understand adversary behavior and improve defenses. It also supports threat hunting and red team exercises.

Target benchmark: Above 75% coverage for mature SOCs.

How Can I Improve Security and SOC Metrics?

Improving metrics starts with fixing the root causes—bad tooling, poor processes, or overworked teams.

Automate repetitive tasks. Use SOAR platforms, workflow automation, or AI-powered security teammates to handle routine alerts like blocking IPs, resetting passwords, or quarantining files—freeing analysts to focus on complex investigations and threat hunting. This drops MTTR and frees analysts for complex work.

Tune detection rules continuously. Review false positives weekly, adjust SIEM correlation rules, update threat intelligence feeds, and disable alerts that consistently prove benign. Track tuning impact on false positive rates to measure improvement.

Prioritize by risk and business impact. Not all alerts are equal. Implement asset criticality tagging based on the CIA triad (Confidentiality, Integrity, Availability) and business value—distinguishing crown jewels from dev environments. Focus detection and response resources on threats targeting high-value systems first.

Improve MTTD with better visibility. Deploy EDR, NDR, and log aggregation to catch threats faster. Gaps in visibility mean attackers can hide longer.

Reduce MTTR with clear, tested playbooks. Document step-by-step response procedures for common scenarios—phishing, ransomware, insider threats—and automate the repeatable steps. Analysts should spend time on analysis and decision-making, not on routine execution tasks.

Benchmark against peers. Compare your metrics to industry averages. If your MTTR is 10 hours and the industry average is 2 hours, you have a problem.

Invest in continuous training. Analyst speed and accuracy improve with deeper understanding of threat patterns, tool capabilities, and investigation techniques. Cross-train team members across Tier 1 and Tier 2 responsibilities to reduce escalation bottlenecks and improve coverage during absences.

Monitor metrics that are outcome-based. Instead of celebrating “alerts closed,” one should begin monitoring “risk reduced.” It should be asked whether this work has increased our safety

Research shows that organizations implementing AI-driven automation can reduce MTTR by 45% and MTTD by 30%, though results vary based on implementation quality, integration with existing tools, and analyst adoption. The key is measuring improvement, not just deploying tools.

FAQs

Conclusion

One question must be answered by the SOC metrics: Do we decrease risk? To gauge velocity, keep an eye on MTTD as well as MTTR. To detect noise, monitor false alarms. Measuring automation will release your team. Rather than following irrelevant data, you should monitor that which safeguards your business.