What are some leading indicators that predict SOC performance?

This article explores SOC capacity planning and how leading indicators shape operational performance, featuring insights from Ben Brigida and Ray Pugh, SOC operations leaders at Expel.

The complete interview can be found here: How to measure a SOC

SOC capacity refers to the total available resources—primarily analyst hours and operational throughput—that a security operations center (SOC) can dedicate to monitoring, detecting, investigating, and responding to security threats. Understanding and managing capacity effectively is essential for maintaining service quality while protecting analyst wellbeing, particularly since cybersecurity teams don’t control when threats emerge—attackers set the tempo.

 

How do leading indicators shape downstream metrics?

Leading indicators like alert volume and volatility directly predict downstream operational SOC performance. When alert volume spikes unexpectedly, organizations face a critical decision point. The wrong response—telling analysts to work harder and faster—creates a cascade of negative effects: corner-cutting, quality degradation, incomplete investigations, and eventual burnout.

The right approach increases throughput by adding capacity, whether through surge staffing, managed security services, or strategic automation. This maintains quality standards while accommodating increased demand. However, implementing the right approach requires advance planning—when an alert spike is happening, it’s too late to develop a response strategy.

Effective capacity management starts with awareness of three critical factors: available capacity (how many analyst hours you have), seasonality patterns (predictable fluctuations in demand), and preparation for unpredictable spikes (because in cybersecurity, threats don’t follow business calendars).

 

Understanding capacity utilization

Capacity utilization—the percentage of available analyst time spent on productive work—serves as one of the most important health indicators for SOC performance. The challenge lies in finding the right balance.

Too low utilization suggests inefficiency and wasted resources. Too high utilization creates burnout risk and quality problems. Leading SOC operations typically target utilization between 70-80%, providing buffer capacity for unexpected surges while maintaining analyst engagement and wellbeing.

Organizations targeting near-100% utilization inevitably sacrifice essential activities like training, documentation, knowledge sharing, and strategic improvements. This short-term efficiency gain creates long-term SOC performance problems as quality degrades and analyst turnover increases. 

 

Utilization level	Operational impact	Recommended action
Below 60%	Potential inefficiency, underutilized resources	Review workload distribution and alert tuning
60-70%	Healthy range with good buffer capacity	Monitor for trends, maintain current approach
70-80%	Optimal range for most operations	Continue monitoring, prepare surge capacity
80-90%	Warning zone—limited surge capacity	Plan capacity additions, accelerate automation
Above 90%	Critical—burnout and quality risk imminent	Immediate action required to add capacity

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What drives unexpected alert spikes?

Alert volume rarely remains constant. Understanding common spike causes enables better preparation and faster response to maintain SOC performance.

Vendor signature updates represent one of the most frequent culprits. Security tools regularly update detection signatures, and occasionally these updates generate excessive false positives. A signature designed to detect malicious activity might inadvertently alert on benign processes like common browser files, flooding the SOC with thousands of meaningless alerts.

Environmental changes like major system updates, new application deployments, or infrastructure migrations can trigger alert surges as security tools detect unfamiliar activity patterns that may appear suspicious.

Active threat campaigns drive legitimate alert spikes when new widespread threats emerge. Zero-day vulnerabilities or major malware campaigns generate increased detection activity across the security stack.

Configuration errors in security tools or newly deployed detection rules can create alert floods until identified and corrected.

 

The critical importance of rapid diagnosis

When alert spikes occur, having the right levers to pull quickly makes the difference between controlled response and operational chaos that can severely impact SOC performance. Effective SOC operations require diagnostic capabilities that rapidly identify what’s causing queue volatility.

Dashboards visualizing alert patterns by source, type, severity, and timing help analysts quickly pinpoint problems. Is a single vendor tool generating the spike? Does the surge correlate with a recent signature update? Are alerts clustering around specific file hashes or network indicators?

Quick diagnosis enables targeted responses. For spikes caused by false positives from vendor updates, suppressing specific alert types or adjusting detection rules provides immediate relief. For spikes from genuine security events, pulling in surge capacity prevents analysts from becoming overwhelmed while maintaining thorough investigation standards.

Technology solutions work for certain spike types, while others require manual intervention and additional resources. The key is having both capabilities available and knowing which to apply in different scenarios.

 

Never tell analysts to work harder

This principle stands as perhaps the most important insight in capacity management. When capacity constraints emerge, the natural impulse is to push for increased individual output. This approach always backfires.

Telling analysts to work faster inevitably degrades quality. Rushed investigations miss critical details. Documentation gets skipped. Corner-cutting becomes normalized. The organization trades short-term queue management for long-term operational problems and security gaps.

As organizational theorist W. Edwards Deming observed, a bad system beats a good person every time. Capacity problems stem from system-level issues—insufficient staffing, poorly tuned detections, inadequate automation, or process inefficiencies. Individual analysts cannot fix system problems through harder work, and pushing them to do so only degrades SOC performance. 

Effective SOC management focuses on system improvements: removing obstacles, implementing automation, tuning detections to reduce false positives, and adding capacity when sustained high utilization signals insufficient resources. These changes enable analysts to maintain quality standards while handling increased workloads.

 

Building flexible staffing models

Since security operations face both predictable seasonality and unpredictable spikes that can dramatically affect SOC performance, capacity planning requires flexibility. Several approaches enable organizations to scale capacity dynamically:

Hybrid staffing models combine internal security staff with external managed services, providing the flexibility to increase capacity during surges without the long lead times associated with hiring and training full-time employees. This approach proves particularly valuable for organizations experiencing rapid growth or facing persistent cybersecurity talent shortages.

Cross-training initiatives develop analysts who can work across multiple security domains, enabling dynamic capacity reallocation. When endpoint alerts surge, cross-trained analysts from network security can assist with triage and initial investigation.

Surge capacity partnerships with contractors, temporary staff, or managed detection and response providers enable rapid augmentation during major incidents or sustained alert spikes. The key is establishing these relationships before they’re needed, with clear processes for rapid activation.

 

Need data-driven capacity insights?

Download Expel’s free SOC Metrics Dashboard to track utilization, identify bottlenecks, and make informed staffing decisions.

 

Monitoring leading indicators

Proactive capacity management depends on monitoring indicators that predict future SOC performance problems before they become crises.

Alert volume trends reveal patterns that inform capacity planning. Tracking daily, weekly, and monthly alert patterns identifies seasonality, growth trends, and anomalies requiring attention. Statistical change-point analysis can automatically detect significant shifts in alert patterns, enabling rapid response to emerging issues.

Queue depths and wait times signal capacity constraints before quality degradation becomes apparent. When alerts wait increasingly long for analyst attention, it indicates that incoming work exceeds throughput capacity. Addressing the imbalance before quality suffers prevents customer impact and analyst stress.

Utilization rates require continuous monitoring. Sustained utilization above 85% signals imminent problems. Even before analysts consciously feel overwhelmed, high utilization degrades performance through increased cognitive load, reduced attention to detail, and accumulated fatigue.

Incident response loading affects routine capacity since major incidents consume senior analyst attention for extended periods. Organizations should track what percentage of capacity goes to incident response versus routine operations, ensuring sufficient reserves to handle major incidents without creating unsustainable backlogs.

 

The connection between capacity and quality

Capacity management and quality control represent two sides of the same operational coin. Insufficient capacity degrades SOC performance, while poor quality operations waste capacity.

When analysts lack sufficient time for thorough work, investigations become rushed and documentation suffers. This creates immediate quality problems and long-term knowledge gaps. Poor initial investigations often require revisiting, consuming double the capacity of thorough first-pass analysis.

Conversely, quality problems consume excess capacity. Poorly tuned detections generating high false positive rates waste analyst time on low-value alerts. Inefficient processes requiring manual work for automatable tasks consume capacity without improving security posture. Organizations should view quality improvements and automation initiatives as capacity expansion strategies.

 

SOC capacity FAQ

What’s the right capacity utilization target?

Most effective SOCs target utilization between 70-80%. This allows handling routine workloads while maintaining buffer capacity for incidents and unexpected surges. Utilization consistently above 85% signals burnout risk.

How do we handle vendor-caused alert spikes?

Rapid diagnosis is critical. Identify which vendor and detection rule is generating the spike, then determine if it’s a false positive issue or legitimate detection. For false positives, quickly adjust or suppress the problematic rule. For legitimate detections, activate surge capacity to handle increased workload.

Should we add headcount or improve automation first?

The answer depends on current utilization. If analysts consistently operate above 85% utilization, add capacity immediately to prevent burnout while developing longer-term automation solutions. If utilization is lower, prioritize automation and detection tuning to increase throughput before adding staff.

How does seasonality affect capacity planning?

Many organizations experience predictable patterns—lower alert volumes during holidays, spikes during peak business periods, or increased threats during specific seasons. Understanding these patterns through historical analysis enables proactive staffing adjustments to match anticipated demand.

What metrics should we track for capacity planning?

Start with fundamentals: total available analyst hours, actual utilization percentage, alert volume trends, queue depths, and investigation cycle times. These metrics provide visibility into capacity health and early warning of emerging problems.

 

Getting started with capacity planning

Organizations beginning capacity planning efforts should focus on fundamentals before pursuing sophisticated approaches:

Begin by measuring current state—document total available analyst hours, track how time is spent across activities, and establish baseline utilization metrics. This provides the foundation for informed decisions.

Implement basic monitoring for alert volume, utilization rates, and queue depths. Simple dashboards providing visibility into these metrics enable proactive management.

Develop response playbooks for common scenarios like alert spikes or major incidents, so teams know how to respond before crises occur. Planning while calm proves far more effective than improvising during emergencies.

Finally, consider whether partnership with managed security services makes sense. Given persistent talent shortages and the complexity of capacity management, many organizations find that managed SOC services provide better SOC performance and security outcomes at lower cost than building and maintaining internal capacity.

 

How Expel manages capacity

At Expel, we’ve built our operation around sustainable capacity management that eliminates constraints for customers while maintaining analyst wellbeing. We maintain significant analyst capacity across global time zones for genuine 24×7 coverage, and we continuously monitor capacity metrics to make proactive staffing decisions well before constraints impact operations.

Critically, we never ask analysts to work faster. Instead, we invest continuously in automation and detection tuning to increase throughput. Our security operations platform handles routine tasks, enabling analysts to focus on complex decisions requiring human expertise. When alert spikes occur, we have diagnostic capabilities and technical levers to rapidly identify causes and implement solutions.

 

Ready to eliminate capacity planning overhead?

Learn about Expel’s comprehensive managed detection and response services that provide scalable, expert-driven security operations without capacity management concerns.

Resources for SOC capacity planning

Organizations developing effective capacity planning strategies can benefit from additional resources and industry guidance:

• Performance metrics, part 1: Measuring SOC efficiency explores foundational metrics for understanding capacity, utilization, and alert patterns
• Performance metrics, part 2: Keeping things under control addresses change-point analysis and statistical techniques for detecting alert volume shifts
• Stressed SOC? Data’s your best ally to justify more resources provides practical frameworks for calculating analyst utilization and communicating staffing needs
• How much does it cost to build a 24×7 SOC? examines staffing requirements, shift models, and budget considerations for internal SOC operations
• 7 habits of highly effective SOCs discusses capacity management, automation strategies, and preventing analyst burnout
• What is SOC-as-a-service (SOCaaS)? explores managed SOC services as an alternative to building internal capacity
• SOC metrics dashboard tool provides a free downloadable resource to track utilization, capacity, and key performance indicators

Effective capacity planning enables SOC operations that protect organizations without burning out analysts. Organizations that monitor leading indicators, respond proactively to capacity constraints, and maintain healthy utilization levels create sustainable security operations that can adapt to evolving threats while maintaining consistent quality and analyst wellbeing.