In 1944, engineers started circulating a brilliantly satirical technical description. The “turbo encabulator” supposedly used “a base plate of prefabulated amulite” to achieve “reciprocation of dingle arms to prevent side fumbling.”
The joke? It was complete gibberish dressed up in impressive-sounding terminology.
I’d argue that today’s hiring process deserves the same diagnosis. And as this rigorous scientific poll shows, 79.8% of today’s workforce agrees with this conclusion with a correlational coefficient of an unheard of .82.
Consider this. We’ve built elaborate systems – competency matrices, skills assessments, personality profiles, behavioral interviews with STAR frameworks – that soundrigorous and scientific.
But here’s the uncomfortable truth: most organizations have no idea whether their hiring processes actually work.
They don’t track quality of hire. They don’t calculate false positive or false negative rates that indicate if weak people are being considered in favor of strong ones who aren’t. They couldn’t tell you whether interview scores correlate with post-hire performance ratings.
They operate on faith, not evidence, and here’s the huge cost of that faithin hiring mistakes and missed opportunities.
The Correlation Coefficient Shell Game
HR vendors love citing validity coefficients. A cognitive ability test with .51 validity! Structured interviews at .54! These numbers are presented as proof their tools “work.”
This course on LinkedIn learning on data analytics: aka, “Moneyball for HR!” describes how to separate vendor fact from fiction. The major highlight that almost no one tells you:
… correlation coefficients only show direction, not magnitude. To understand actual predictive impact, you must square the correlation.
When you do that, the picture changes dramatically:
- Structured interviews (.51) → Explains only 26% of performance variance
- Cognitive ability tests (.31 after Sackett’s 2022 revision) → Explains less than 10%
- Years of experience (.18) → Explains 3.2%
- Education level (.10) → Explains 1%
- Skills-based hiring (???) → It’s unclear how much this actually helps improve post-hire success.
Read that again. Even the best selection method explains barely a quarter of why someone succeeds or fails. The most common job requirements – years of experience and degrees –explain almost nothing. Nothing!
The Skills-Based Hiring Mirage
HR leaders are being told that skills-based hiring will transform selection over the next 3-5 years. Remove degree requirements. Use AI-powered skills taxonomies. Match talent to opportunity with precision.
One question: Where’s the evidence that shifting to skills will improve hiring results?
Despite billions invested in skills assessment platforms, rigorous scientific proof that skills-based hiring improves outcomes is remarkably thin. Most skills assessments have unknown validity. Companies adopt them based on vendor promises, not independent validation.
The irony is brutal: we’re replacing one unvalidated practice (credential screening) with another unvalidated practice (skills screening) while ignoring the methods that actually have scientific support like work samples, structured assessments, cognitive ability, and learning agility.
The Real Root Cause – Attraction Is Far More Important Than Selection
Here’s what selection validity research almost entirely ignores: What if the problem isn’t who you select from your applicant pool, but who’s in your applicant pool in the first place?
Organizations spend heavily on improving selection precision while underinvesting in attraction quality.
It turns out that the strongest candidates are rarely found through job ads — they are found through relationships, reputation, and compelling work using Career Hubs like this one.
What Actually Works for Selection
When you integrate insights from I-O psychology, Gallup’s engagement research, John Doerr’s OKR framework, and Todd Rose’s science of individuality, a different approach emerges. One that’s also legally defensible.
Reject “average” thinking. Todd Rose’s research in The End of Averagereveals a mathematical fact: no one is average. His “jaggedness principle” shows that talent is never one-dimensional. When we compress candidates into single scores or filter by rigid requirements, we systematically overlook exceptional talent.
Define jobs as performance objectives, not skill lists. “Reduce customer churn by 15% in year one” attracts different candidates than “5+ years experience and Salesforce proficiency.” You can convert any skill into a performance objective by answering this question: What does the person need to do with the skill to be considered successful?
Assess past performance, not hypothetical responses. The most replicated finding in personnel psychology: past performance predicts future performance in comparable situations. To assess this during the interview look for the achiever pattern indicating evidence of growth, performance and learning agility.
The turbo encabulator was funny because engineers recognized the absurdity. The hiring encabulator isn’t funny because most people don’t recognize it. They believe personality tests predict performance, that years of experience indicate competence, that skills assessments measure what matters.
The evidence says otherwise.
You can continue investing in sophisticated-sounding processes that don’t work. Or you can adopt evidence-based approaches that do: attraction that draws achievement-oriented candidates, selection that assesses demonstrated patterns of growth, and post-hire engagement that provides clarity and support.
Your choice.