Cary, NC, March 24, 2026 (GLOBE NEWSWIRE) — As enterprise organizations face increasing pressure to justify technical spending, many are discovering that traditional training models are quietly wasting budget. According to internal market analysis from INE Security, organizations that benchmark technical skills before assigning training can reduce annual training spend by as much as 30% by eliminating unnecessary coursework and focusing development where it is actually needed.
INE Security, a global provider of networking and cybersecurity training and certifications, today outlined how organizations are shifting from broad training assignments toward assessment-driven workforce development, using the company’s Skill Sonar platform to identify technical skill gaps and assign targeted learning paths.
Traditional training programs often rely on universal seat licenses or broad learning assignments that assume teams require the same development. In practice, this can lead to experienced practitioners repeating material they already understand while critical skill gaps remain unaddressed.
By benchmarking skills before assigning training, organizations can focus resources on the individuals and competencies that require development.
“Organizations can’t afford to guess where skills gaps exist,” said Lindsey Rinehart, Chief Executive Officer at INE. “When teams assess first and train second, they gain visibility into their real technical capabilities and can focus training investments where they have the greatest operational impact.”
Moving Beyond One-Size-Fits-All Training
INE’s Skill Sonar platform provides real-time technical skill assessments that help organizations measure proficiency across cybersecurity and networking domains. Instead of assigning training broadly across a team, leaders can identify which individuals need development in specific areas and assign learning accordingly.
Skill Sonar assessments evaluate practitioner capabilities across multiple domains, including:
- Blue Team Essentials
- Red Team Essentials
- Yellow Team Essentials
- Enterprise Infrastructure Networking
- Network Security
- Cloud Infrastructure
Results provide a clear view of current proficiency levels across individuals and teams, allowing organizations to identify skill gaps quickly and prioritize training efforts.
Turning Assessment Data Into Targeted Learning
Once assessments are completed, Skill Sonar automatically generates personalized training playlists tailored to each learner’s performance. These playlists adapt as practitioners progress and reassess their skills, ensuring that development paths remain aligned with their evolving capabilities.
This targeted approach helps organizations:
- Eliminate unnecessary training for experienced practitioners
- Focus development on the areas where skills gaps exist
- Accelerate skill improvement across teams
- Simplify training program management for technical leaders
By aligning training directly to assessment data, organizations can build stronger teams while improving the efficiency of their training investments.
Building Stronger Technical Teams Through Skills Visibility
Beyond improving training efficiency, skills benchmarking provides leaders with valuable insight into team readiness across several operational priorities, including infrastructure stability, regulatory compliance, and workforce development.
With real-time assessment data, technical leaders can better understand where teams are strong, where additional training is needed, and how development efforts are progressing over time.
“Technical leaders need more than course completion metrics,” said Tiana Harman, Director of Product at INE. “They need visibility into what their teams can actually do. Skill Sonar helps organizations measure technical proficiency and turn that data into targeted learning strategies.”
Availability
Skill Sonar is available through INE’s enterprise training platform and integrates with the company’s cybersecurity, networking, and cloud learning paths.
For more information, visit https://ine.com/sonar.
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