Look beyond job titles and credentials to understand what candidates can actually do. Rami Albatal explores why skills-based hiring often fails to deliver meaningful hiring change, how task level data can uncover overlooked talent, and why closer collaboration between recruitment and learning teams can strengthen internal mobility and hiring outcomes.
Talent leaders today describe hiring differently than they did a few years ago. They talk more about skills, what people can do, rather than the credentials and previous roles they flaunt. The World Economic Forum (WEF) expects 39% of workers’ core skills to change by 2030 thanks to AI, so it’s logical to see recruiters acknowledging that titles can only tell us so much about what a candidate can do.
That gap between what recruiters try and whom they hire holds the key to the puzzle of why skills-based hiring
The results of skills-based hiring strategies, however, have been oddly muted. When Harvard Business School and the Burning Glass Institute examined the results of large employers dropping degree requirements, they found that fewer than one in 700 hires benefited from the supposed increase in opportunity. That gap between what recruiters try and whom they hire holds the key to the puzzle of why skills-based hiring, despite being a genuinely good idea, tends to stall so often. Let’s take a look.
Dropping the degree was the easy part; the job title is next
Degree requirements are a fast and, admittedly blunt, filter that seeks to measure capability before anyone can make a hands-on judgment. Job titles do the same job. When you stop thinking about degrees, you’ll lose that filter and recruiters will be left reading the same applications with less to work with than before.
The resulting gap will likely be filled by whatever remains. Recruiters may lean on the name of a previous employer, the seniority a job title implies, or their experience. While such proxies may stand out, they often prove weaker than the credentials they replace, which narrows the very funnel we sought to widen when we dropped the degree requirement.
The Harvard study illustrates this clearly: Across 11,300 roles, firms that removed degree requirements raised their share of hires who didn’t have a degree only by a fraction of a percentage point.
The qualified people a title search never sees
When done well, skills mapping can help recruiters find the people a conventional search cannot. Such candidates tend to fall into two groups.
People in the first group usually work in an adjacent industry. Think: An operations coordinator may have spent years pruning data, studying it, building dashboards and automating reports, but few search queries built around the label “data analyst” will show you her profile because her job title gives you information about her department, not her ability.
The second group are close to home, often one grade below the role that needs filling. These people stay hidden because the official profiles for their current grade and the target grade were written years apart by different people. The skills were never lined up in a way an automated system could match them.
Internal hires usually cost less to bring on, reach full speed sooner, and already know how the organisation works. Finding that person is as much a job for learning and development (L&D) as for recruitment.
However, skill labels, on their own, are a coarse measure of a candidate’s capabilities. A project manager in construction and a project manager in software may share most of their listed skills, but they do markedly different jobs.
Understanding what someone can do requires looking past the labels. Tasks sit at a level below skills and are less ambiguous, as they describe actions rather than ability. Increasingly, that lower level is where both hiring, and performance assessment are finding firmer ground.
How to tell if your approach is working
The discipline of naming the outcome metric before you start is what separates the programmes that work from the ones that drift. Here are two indicators to watch for:
- The most accurate indicator is how long you take to fill the roles that stay open the longest. Blended time-to-hire figures are a weak measure of this, since they also account for roles that were never difficult to fill in the first place.
Narrow the lens to the thin end of the market, and you’ll see the signal quickly. If widening the search from job titles to capability works for you, those difficult-to-fill roles will start filling faster. If they stay empty, revisit your approach. - The other indicator is harder to move without genuine change: the share of vacancies filled from within, set against what an internal move costs versus an external hire.
This number usually only climbs when recruiters and the L&D team work from the same record of skills, and it’s often the one that CFOs care about, since internal candidates cost less to replace.
Expect these indicators to move in sequence. Focus on the groundwork of describing your talent and the tasks they do, across only crucial roles, before your strategy goes live. Once you have that data foundation in place, you’ll see the difficult roles being filled faster first. Internal mobility may take longer to tick up, since promotions run on longer cycles. Use what works as evidence to expand the project.
When such a hiring program stalls, two mistakes are usually the cause. Organisations often mess up the scope of the exercise, seeking to map skills and hire accordingly across the whole enterprise in a single wave. The other is drift, where busy recruiters slide back to the proxies they trust.
The barrier was never the ambition
Skills-based hiring has always been held back by the labour of describing every role and every person in one consistent language. It’s an exercise that once ran for years and now, thanks to AI, takes only weeks.
That change is what finally makes a skills-based hiring strategy testable, and employers are now committing to it in numbers. The WEF found that 85% of employers now plan to prioritise upskilling their workforce, and 70% expect to hire staff with new skills.
When hiring goes skills-first, recruitment and L&D stop being separate disciplines running on separate data. In a title-based world, the recruiter’s language (job titles, requisitions, years of experience) and the L&D language (competencies, courses, learning paths) barely intersect, which is why the two functions have historically found it so hard to act as one system.
Once an organisation describes its roles and its people in a common skills language, “should we hire this or build this?” becomes a single question answerable from the same data, and that approach repositions L&D from a support function into one that plans the workforce.
Rami Albatal is Head of AI at Beamery
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