Eight times the output. Same job. Same title. Not 80%. 800%. That’s a lot. And yet, most hiring systems and processes are almost perfectly designed to miss those people. This isn’t a talent shortage. We’ve normalized a measurement problem for so long that it barely registers as a problem anymore.
Across industries, hiring has been optimized for efficiency and familiarity. We screen for credentials that look impressive, resumes that read cleanly, and career paths that resemble the ones we already trust. It feels rigorous. It feels fair. But it isn’t actually predictive of performance. In fact, the more polished a hiring process becomes, the more likely it is to filter for sameness—and against the very capabilities that drive outsized performance.
Much of this starts with technology that was designed for process automation and then tried to evolve to deliver objectivity at scale. Keyword-based applicant tracking systems move fast, but speed comes at a cost. These systems reward precise phrasing and conventional formatting, not capability. A candidate who has done the work—but describes it differently—never makes it through. These systems weren’t built for filtering talent in—they were built to filter talent out.
Manual review is often held up as the antidote, but it brings its own limitations. Humans are better at nuance, but we’re also deeply patterned. The 3-pound caloric monsters we carry around in our skulls are designed for pattern recognition and the path of least resistance. By genetics, we gravitate toward what looks familiar and overvalue signals that feel safe. And even when intentions are good, unstructured evaluation consistently misses qualified candidates—while remaining impossible to scale.
And then, the elephant in the room: Teams are really stretched. Thoughtful, consistent, manual review is less and less feasible, leaving organizations stuck in an uncomfortable middle. Do we settle for technology that is efficient but blind, or humans who are thoughtful but inconsistent? Neither reliably captures what actually predicts performance.
DISTANCE TRAVELED
This isn’t a new problem.
Two decades ago, medical schools ran into the same issue. Traditional admissions criteria—grades, test scores, pedigree—were effective at predicting who could pass exams. They were far less effective at predicting who would become exceptional physicians. The metrics were clean. The outcomes were not.
So some institutions started asking different questions. Not just How did this person perform? but How far did they travel to get here? What obstacles did they face? What did they have to figure out without a playbook?
This idea—often referred to as distance traveled—impacted who was admitted. And it changed outcomes for the better. Students selected under these frameworks didn’t just keep up—they set the bar. They demonstrated stronger judgment under pressure, greater adaptability in ambiguous situations, and deeper empathy with patients whose lives looked nothing like their own.
Corporate hiring is now facing a similar time in history, a convergence of inflection points.
In fast-moving business environments, the skills that matter most rarely show up neatly in job titles or degrees: learning quickly; thinking clearly when information is incomplete; staying resourceful when plans fall apart; persisting when there’s no obvious path forward. These aren’t “soft skills.” They’re critical performance and leadership skills and they’re largely invisible in traditional screening. And that’s bad. It’s bad for innovation, it’s bad for culture, it’s bad for the bottom line. The cost of getting this wrong shows up everywhere.
Most employers will admit they’ve made at least one bad hire in the past year. The financial impact of that is relatively easy to calculate. The less visible damage—lost momentum, exhausted teams, opportunities that never materialize—is harder to measure, but no less real. What’s even harder to see or measure is the impact of the lost talent that never had a chance to contribute. The career changer who learned fast because they had to. The veteran who led teams under pressure but doesn’t speak corporate. The self-taught professional who mastered complex systems without a credential to legitimize it. These candidates have already demonstrated the capabilities companies say they want, but they don’t look as “shiny” on paper.
CHANGE WHAT YOU MEASURE
All is not lost. Some organizations are starting to respond—not by lowering standards, but by changing what they measure. Instead of defaulting to credentials and pedigree, they’re evaluating skills directly. They’re using assessment questions about real-world scenarios, samples, or actual work, and problem-solving exercises that reflect the actual demands of the role.
The shift is delivering significant organizational impact. Research shows that when hiring is grounded in capability rather than convention, candidate pools widen. Quality improves. Competition for the same narrow band of “perfect” resumes eases. But the real advantage runs deeper than these metrics.
CAN COMPANIES AFFORD NOT TO EVOLVE?
Traditional hiring was built for a world where careers were linear and jobs changed slowly. In that world, past experience was a reasonable proxy for future performance. That world is gone! Today, the defining advantage isn’t what someone already knows—it’s how quickly they can learn what comes next.
Medical schools recognized this years ago. They stopped over-indexing on metrics that predicted short-term success and started evaluating for the human capabilities that predict excellence over time. The corporate world needs to catch up.
The question for CEOs and CHROs isn’t whether hiring should evolve. It’s whether organizations can afford not to evolve and to just leave enormous performance upside untouched. Because somewhere in your applicant pool is a candidate who figured things out the hard way or who learned faster because they had fewer options. Someone who developed exactly the capabilities your business needs next.
Your systems may never notice them, but someone else’s will.
Natasha Nuytten is CEO of CLARA.