Latest / Hiring & Firing with Fexingo: Recruitment, Performance, and Workforce Decisions / How Hiring Managers Inflate Job Requirements and Block Candidates
Transcript
- Lucas: We talk a lot on this show about how hard it is to find good people. But there's a quieter problem that doesn't get nearly enough attention: hiring managers who inflate job requirements until the ideal candidate is basically a unicorn. Luna: You mean the 'must have ten years of Python experience' when Python's only been around for, what, 30 years? That kind of thing? Lucas: Exactly. A National Bureau of Economic Research working paper from late 2025 analyzed 20,000 job postings across 10 industries and found that over 60 percent of job requirements had no statistically significant correlation with job performance. Let that sink in: the majority of things hiring managers ask for don't predict whether someone will actually be good at the job. Luna: So they're adding requirements out of habit or fear, not data. Lucas: Right. And the cost is enormous. Every extra requirement shrinks the candidate pool. One analysis from the same paper estimated that adding a single 'nice to have' credential — like 'certification in X' or 'five years of Y' — reduces the applicant pool by roughly 15 to 20 percent. Layer on a few of those, and you're down to a sliver of people, many of whom are overqualified and will leave within a year. Luna: I've seen this firsthand. At a previous company, a hiring manager insisted on a CFA for a financial analyst role that didn't even involve portfolio management. They ended up waiting six months to fill it. Lucas: And that's the paradox. The manager thinks they're being rigorous — 'I want someone who really knows the field.' But what they're actually doing is screening out candidates who could learn the job quickly and bring fresh perspectives. The NBER research found that jobs with fewer stated requirements actually had lower turnover and higher performance ratings after six months. Luna: Because you're not filtering for things that don't matter. You're letting in people who can actually do the work. Lucas: Exactly. There's a company called VeroCloud — mid-size SaaS, about 800 employees — that went through a full job description audit in 2023. They had a director of engineering who was requiring '10 years of cloud infrastructure experience' for a mid-level DevOps role. The problem? AWS itself only launched in 2006. So 10 years of cloud experience meant the candidate would have to have started in 2013 at the earliest, when AWS was already mature. They were effectively excluding everyone who'd grown up with cloud-native tools. Luna: That's absurd. Did they fix it? Lucas: They did. The head of talent acquisition forced a line-by-line review of every job description. For each requirement, they asked: 'Is this something the person will use in the first 90 days? And is there a measurable difference in performance between someone who has it and someone who doesn't?' They cut the average number of requirements from 12 down to 6. time to hire dropped from 55 days to 33. And quality of hire — measured by manager satisfaction after six months — actually went up. Luna: So the real issue isn't just habit. It's that hiring managers don't want to be wrong. If they set the bar high and the hire fails, they can say 'well, we had high standards.' But if they set a low bar and the hire fails, it's on them. Lucas: That's a huge part of it. It's called 'CYA hiring' — cover your ass. You list everything you can think of so if the person doesn't work out, you can point to the resume and say, 'look, they had the credentials.' But the data shows that credentials are a weak predictor of performance. What matters more is the ability to learn, adapt, and collaborate — things you can't screen for with a checkbox. Luna: And there's a darker side too. Some hiring managers use inflated requirements to exclude candidates they're biased against. If you don't want to hire someone from a certain school or background, you add a requirement that you know they won't meet. Lucas: The NBER paper found evidence of exactly that. In industries where gender or racial bias is documented, job postings had significantly more 'nice to have' requirements — things like 'must have published in top-tier journals' or 'must have experience with specific legacy systems.' These were coded ways to narrow the pool to a familiar demographic. It's insidious because it looks like rigor, but it's discrimination by checklist. Luna: So what's the fix? How do you get managers to stop padding requirements? Lucas: The first step is making the requirements visible and measurable. At VeroCloud, they built a simple dashboard that showed the number of requirements per job, the average tenure of candidates, and the subsequent performance score. When managers could see that their 12-requirement job was taking twice as long to fill and producing hires with lower scores, they started trimming voluntarily. Luna: So you're using their own data against them. I like that. Lucas: The second step is a 'two-tier' system. Distinguish between 'must-haves' — things the candidate absolutely needs on day one — and 'nice to haves,' which are explicitly labeled as optional. The VeroCloud team found that when they labeled something as 'nice to have,' the applicant pool doubled, and the quality didn't drop. Managers still got to see the nice to haves in the resume, but they weren't used as screening gates. Luna: That's a simple change that could have huge impact across the board. Lucas: And it's not just about efficiency. It's about fairness. When you strip away the inflated requirements, you open the door to candidates who might not have the traditional pedigree but have the raw ability. That's how you build a more diverse and resilient workforce. Luna: Yeah, and it's also just more honest. You're not pretending the job is harder than it is. Lucas: If these conversations have moved your work forward in some small way, a couple of dollars a month is genuinely what keeps these going — buy me a coffee dot com slash fexingo, if you've gotten something out of them. Luna: It's small amounts that make a real difference. We don't run ads, so listener support is how we stay independent and focused on the stuff that matters. Lucas: Alright, back to the data. One other thing the NBER study found was that jobs with very short, bare-bones descriptions — just 'we need someone to do X' — actually attracted more qualified applicants on average. Because the signal was clear: we know what we need, and we're not wasting your time. Luna: So the lesson for hiring managers might be: write the job description like you're writing it for yourself. If you wouldn't apply for it, why would anyone else? Lucas: Exactly. And if you're a candidate, and you see a job with 15 requirements, maybe take that as a red flag. It might mean the manager doesn't know what they actually need — and you'll spend your first six months unlearning their assumptions. Luna: That's a good note to end on. Less is more, in job descriptions and in hiring. Lucas: Next episode, we're looking at something a bit uncomfortable: why some of the best hires are people who were fired from their last job. Luna: That sounds like a conversation I want to hear.