1 in 700
New hires actually impacted by degree requirement removal, despite 85% of companies claiming skills-based hiring — HBS & Burning Glass, 2024
A growing body of research confirms what organizations already sense: the signals they rely on to evaluate talent are failing them.
These are the studies, data, and insights that shape the RED Talent Intelligence Architecture™ — and the case for a more rigorous approach to recognizing human potential.
— Rahsaan E. Diaz, Founder, RED Intelligence Group
Across industries and institutions, the evidence points in the same direction: the signals organizations rely on to evaluate talent are not the signals that predict performance.
New hires actually impacted by degree requirement removal, despite 85% of companies claiming skills-based hiring — HBS & Burning Glass, 2024
More predictive of job performance: skills-based hiring vs. credential-based hiring alone — McKinsey
Of core job skills expected to change by 2030 — making credential-based screening increasingly obsolete — WEF, 2025
Studies and findings that directly inform and validate the RED Talent Intelligence Architecture™.
Anthropic researchers introduced a new measure of AI displacement risk — observed exposure — tracking which job tasks are actually being automated in professional settings. The findings reframe who is most at risk: workers in the most AI-exposed occupations are more likely to be older, female, more educated, and higher-paid. The workers traditional hiring systems prize most are precisely those most exposed.
Workers with graduate degrees are nearly four times more represented in the highest-exposure group than in the lowest. The earliest labor market signal is appearing not in unemployment — but in hiring: entry into exposed occupations for workers ages 22–25 has declined an estimated 14% in the post-ChatGPT era.
An analysis of over 11,000 job postings across U.S. firms from 2014 to 2023 revealed a stark gap between what companies say and what they actually do. While 85% of organizations claim to practice skills-based hiring, the real change in non-degree hiring amounts to just 3.5 percentage points — impacting fewer than 1 in 700 new hires.
The report classifies most organizations as either "In Name Only" adopters or "Backsliders." Only a small group of "Leaders" sustained change by investing in structural reform: redesigned interviews, new evaluation criteria, and hiring manager development.
Drawing on data from over 1,000 companies representing 14 million workers across 55 economies, the WEF's report identifies the skills gap as the single largest barrier to business transformation — cited by 63% of employers. By 2030, an estimated 39% of core job skills will change, rendering credential-based screening increasingly ineffective.
The fastest-growing skills include both technical capabilities and fundamentally human ones: resilience, adaptability, creative thinking, and learning agility — precisely the signals the RED Capability Signal Model™ is designed to evaluate.
McKinsey's workforce research found that hiring for skills is five times more predictive of job performance than hiring based on educational credentials alone. Organizations that made the genuine structural shift reported a 107% improvement in placing people in the right roles, 98% better retention of high performers, and 40% lower turnover among skills-hired employees.
TestGorilla's State of Skills-Based Hiring reports further document that 91% of companies implementing structured skills evaluations saw reductions in time-to-hire, with 40% reporting a decrease of over 25%.
In one of the most significant re-analyses of hiring science in decades, Sackett and colleagues found that structured interviews — designed to evaluate judgment, decision quality, and behavioral patterns — rank among the strongest predictors of job performance. Years of experience, long treated as a reliable signal, ranks among the weakest — outperforming fewer than 22 other commonly used selection criteria.
The structure of evaluation matters as much as what is being evaluated. Unstructured conversations and résumé reviews produce systematically weaker prediction than structured capability-based assessment.
Brookings researchers identified a foundational barrier to skills-first hiring that goes beyond policy: organizations lack a trusted, efficient infrastructure for evaluating capability. Degree requirements persist not because they are believed to be accurate — but because they are efficient. They reduce applicant pools quickly in the absence of a better system.
Sustainable reform requires new evaluation frameworks, not just new intentions. Without a rigorous alternative that hiring managers can trust, credential-based filtering will continue by default.
Across every study in this body of research, the same deeper capabilities emerge as the true predictors of performance. The RED Capability Signal Model™ was built to evaluate exactly these.
Decision quality under uncertainty — the signal most consistently linked to performance by structured interview research.
Accountability and follow-through — a stronger predictor than title, tenure, or institutional pedigree.
Ability to perform in changing conditions — ranked among the WEF's fastest-growing skills through 2030.
Speed of learning in new domains — increasingly critical as 39% of core skills are projected to shift by 2030.
The meta capability that integrates and amplifies all others — enabling individuals to understand complexity, navigate interdependencies, and make higher-quality decisions over time. As AI handles more tasks, Systems Thinking becomes the most durable human differentiator.
Understanding the research is step one. The next step is understanding how your hiring system measures up.
The Diagnostic Preview is designed for leaders who want to see how their current process may be overvaluing weak signals and overlooking deeper indicators of performance.
If you're exploring how to improve signal intelligence in hiring, RED Intelligence Group would welcome a conversation.