I can't think of a more frustrating and time-consuming task for executives and hiring managers than filtering through an inbox of poor-fit CVs.
Hiring has entered a strange new era, where there is an abundance of applicants, but a smaller chance of finding the person you actually need. The average job opening now draws around 242 applications, and AI has added a new dimension and burden onto employers. Candidates use AI to write and fire off applications without much thought, and employers use AI to screen them. Automated screening software sometimes rejects great candidates for a six-month gap in their CV or a missing keyword, while the AI-written illegitimate applications slip through.
Hiring is like matchmaking, and volume does not mean quality
Anyone who has spent time on a dating app knows that more options do not equal a better fit. You are shown hundreds of potential matches, but the more you swipe, the further away the right person feels.
In contrast, a good matchmaker takes the time to understand both sides — the person and the family they would be “marrying” into — and they pair people on the things that make a match last, rather than surface-level details that look good on a profile. I feel it is a craft the broader recruitment industry has mostly forgotten.
Volume was never the answer to a matching problem. The best finance, data, and senior hires are already employed. They are not sifting through job boards, and they will probably never see the LinkedIn ad.
A specialist role needs a specialist approach
Just like a first date, a good match on paper might not click in real life. A candidate can tick every box on a job specification and still be the wrong hire, and it often comes down to the things you will not find on a CV.
Maybe the role needs someone who thrives in ambiguity, but the applicant does their best work in a stable, structured environment. A candidate might be an exceptional manager, but they struggle to report back in meetings, and the job needs a strong representative in front of the board.
The small things do not show up in a keyword search either, but they do show up when someone takes the time to understand the role, the team, and the person, and asks the right questions. Most bad hires can be traced back to a vague brief that was not interrogated, a good brief that was not followed, or a rush to send a flood of CVs in the hope that one of them sticks.
Why I suggest you narrow the net, on purpose
If you are staring at a full inbox and an empty seat, casting the net wider will only make the problem worse. An example that comes to mind is a recent role we worked on. Based on the job title and initial job specification from our client, it appeared to be a typical software engineering search.
But after spending some time with the client interrogating the brief and discussing what success looked like in the role, we uncovered that they were not really looking for a traditional software engineer at all. What they really needed was someone with a Product Engineering mindset — the ability to own products from concept through to delivery, rather than simply build features.
This completely changed the search strategy. Instead of targeting Senior Software Engineers with Azure experience, our consultant focused on candidates who had worked in product-led environments, owned products end-to-end, and had the commercial thinking and stakeholder engagement skills to make strategic engineering decisions alongside business stakeholders. The result was a shortlist of three candidates, all of whom were strong fits — not a wall of CVs to wade through.
Job titles rarely tell the full story
Taking the extra time when writing a brief or job description will save you days spent on the wrong candidates. Here is my advice to hiring managers: get very specific about what a strong match looks like.
This should include the obvious requirements — qualifications, experience, and proven results — but you can go a layer deeper. Also consider:
- Hard skills: the exact tools, software, or technical knowledge the role requires
- Soft skills: communication style, how they manage people, how they present to senior stakeholders
- Personal values: what motivates them, what they will not compromise on
- Working style: do they thrive with autonomy, or do they need structure and direction?
- Cultural fit: a description of the team and company environment they need to succeed in
Finally, whoever is screening your shortlist needs to use AI screening cautiously. Grant it the volume job — filtering out clearly unqualified applicants — but the final call should be a trained human eye that catches what software wrongly waves through or dismisses.