Your Next Great Hire May Already Work with You: The Case for “Skillspotting”

This transcript has been generated by AI and may contain slight discrepancies from the audio or video recording.

Anne: Hey, it's your favorite co-worker, Anne, and this is the All Things Work podcast. Think about this for a second. How much of what you're actually capable of doing at work is reflected in your job title? Probably not all of it.

Maybe you're a software engineer who has a gift for mentoring and developing people, or maybe you're a salesperson who has quietly become the person everyone asks to troubleshoot their tech problems, but neither skill is part of your official job.

But what if the biggest talent problem at work isn't so much a talent shortage, but rather that talent management needs to get better at seeing all the skill sets organizations already have? That's the idea behind today's conversation because when someone leaves a role or a new position opens up, organizations may be quick to look outside their walls, post the job, and start interviewing external candidates.

But what if the person who could do that job is someone you never actually think to look at until you actually looked at what they can really do? Today's guest calls the practice of finding that talent skill spotting, and we're going to get into why our job titles, resumes, and traditional hiring systems can make it so difficult to really see what people are actually capable of doing, and more importantly, what you can do about it right after this.

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Anne: I am really excited for you to meet our guest today. Tigran Sloyan is the co-founder and CEO of CodeSignal, a skills intelligence platform focused on helping organizations and individuals discover and develop the skills that will shape the future.

He's a longtime advocate for evaluating people based on what they can actually do, not just the credentials on their resume. He's also a TED speaker, a Forbes contributor, and a former Google employee where he worked on education and technology initiatives. Tigran, welcome to All Things Work.

Tigran Sloyan: Anne, thank you so much for having me. I'm looking forward to this conversation.

Anne: Me too. There's a lot to dive into. So let's start with you, Tigran. You've built your career around measuring what people can actually do, and it started with your personal experience at Google. Walk us through what exactly is your definition of skill spotting, and what led you to champion this idea?

Tigran Sloyan: Great question. As you said, it started from my personal experience at Google, and this is more than a decade ago. When I was working at Google, we were hiring a lot, and I was involved in a lot of interviewing. It started to dawn on me that a lot of the ways in which people were being identified at the top of the funnel was essentially just resumes.

A decade ago, skill spotting was keyword spotting. Recruiters were primarily looking for keywords, and keywords are not skills. When I was trying to figure out how to fix the problem, I realized that I grew up with and went to school with a lot of really highly skilled people, and I was hoping that I could get them to apply to Google and be able to get a job because I knew they were very, very good.

From my personal experience, I had spotted their skills, and I had a hunch that they would be very successful if they got the job. But when I referred them, none of them would get an interview. I started to realize that the reason I got the interview and got into Google was that I had gone to MIT, and what was spotted on my resume was the university I had attended and not necessarily my skills. My friends who were highly skilled, because they didn't have that pedigree on their resume, would simply not be invited to interview.

It also started to dawn on me that talent is the most precious resource humanity has. Everything we have today — from the microphone in front of you to electricity to the internet — has been created by skilled and talented humans. And unfortunately, as a society, we've somehow managed to build a system that is not conducive, to say the least, to discovering and developing that talent. Even when people do, against all odds, manage to become highly proficient in certain skills, we're not very good at spotting those skills unless they're reflected in the brand of the companies they tend to be associated with.

Anne: So why do organizations tend to struggle to see that talent even within their own organization, not just externally?

Tigran Sloyan: If you think about what it takes to actually identify skills, you first have to start from the definition of skills. I'm a mathematician at heart and by training, so when people ask me a question, I tend to go to the definition first.

You'll be shocked at how different practitioners' definitions of skills are, so you have to really dig to figure out what a skill actually is. The proper industrial-organizational psychology definition, especially for work-related skills, is that these are psychological attributes that enable humans to complete work-related tasks. Completing work-related tasks is the key there — that is essentially the anchor of the definition.

What that definition means is that if you're going to understand someone's skills — if you're going to be able to spot them — you have to essentially observe them doing the task that is required for that work, and that is not easy to do. You have to either analyze all the work that they do — and in the recruiting use case, if they work at a different company, there's no way to do that — or you need to be able to simulate the process of somebody doing it, kind of like a flight simulator through which pilots go to prove they can fly the plane before getting on a real one.

Both of those things are not easy to do, and that's the only proper way of doing it. Especially a decade ago, it was not even an option from a technological standpoint, which is why getting on that journey to discover and develop the skills that will shape the future, and to build a way to identify skills, has been a lifelong journey for me.

Anne: I love your term skill spotting because earlier this year SHRM coined a term called skill fishing — that's when candidates look far better on paper than they turn out to be once hired for the job, similar to the experience you've seen while you were at Google. On one hand, we're choosing external hires who may be overselling their skills, and on the other hand, we may be ignoring the proven talent already inside our organizations.

So how do you see these two problems as connected, and what does that say about an employer's default hiring instinct?

Tigran Sloyan: It's very interesting because over the last decade we have helped the industry move towards more of a skills first hiring approach, where everyone coming into the organization has an opportunity to demonstrate their skills in a simulated environment and prove that they have the skills. This allows you to actually spot their skills rather than just rely on keywords, and it allows truly innovative companies to open the funnel for who they are interviewing, because traditionally it has been all about resumes and pedigree.

But that still doesn't fully solve the problem of understanding your own workforce, because that is fundamentally almost more important. Even if you know someone's skill set coming into the organization, a few years in, those things change. With AI today, that has become ever more pressing because jobs are changing. You might hire somebody for a job, and that job might look very different a few years down the line.

It used to take a few years to feel that shift. These days, the timeline of how quickly jobs and skills are changing is compressing every day. So it becomes even more imperative to not just understand the skills your employees have, but also what skills are required to actually do certain jobs. We said skills are psychological attributes to complete work-related tasks — but if you're going to talk about a job, you have to define what set of tasks somebody typically completes in that job, because those are changing, and they're changing very fast.

Anne: They are, and you actually beat me to it because I had a question later about AI, and we're going to dive into that a little bit deeper. But first I really want to dive into what the cost is when companies fail to spot skills properly, either externally or within their own organization. When leaders can't really see the skills in their own workforce, what does that blind spot actually cost their business?

Tigran Sloyan: There are the surface-level, obvious costs, and then there are the deeper ones that I don't think many leaders realize. On the surface, starting from the hiring side, if you fail to spot the skills of people coming in, you're likely going to miss out on talent that could have been transformational for your organization. Or, conversely — similar to the term you described — you think they're skilled, you hire them, and then over the first months and sometimes years, depending on how good your organization is at performance management, you understand that this person is fundamentally ill-equipped to do the job.

It's bad for both the organization and the individual, because as an individual, I want to be in a job I'm competent at. If I'm not competent at the job, I'm going to fail at it, and it's going to be a waste of my time. The cost estimates for making a hire usually run around $20,000 to $25,000 for a single hire. The cost of a failed hire is probably many times higher because of all the time and effort different people across the organization put in to get someone onboarded.

But then if you look internally — moving from hiring to people already in your organization — there are a few different scenarios. One is being able to staff projects appropriately. Especially in larger organizations, there are many different projects where leaders are trying to understand the right team composition. The only way to answer that is to determine who has the skills to perform whatever tasks the project will require. And usually, this is complete guesswork.

You typically go around and ask, "Who do you think?" And humans are humans — we're biased, and we naturally gravitate toward people we like as friends rather than who is actually going to be competent at delivering the tasks at hand. So companies end up staffing teams for certain projects that are, again, fundamentally ill-equipped to deliver.

Then there are the next-order consequences I want to touch on, because if an organization is fundamentally unable to spot skills, it discourages the team from building those skills — and there's a direct relationship there.

Anne: Mm-hmm.

Tigran Sloyan: If, as an employee, I know that my company cannot see and understand my skill set and will not reward me for it through promotions, better jobs, and better opportunities, I'm less likely to pursue new skills. And if I know that growth will go unspotted, I'm more likely to not even bother going through that journey, because it's not easy.

Anybody who has built any skill — and when you think about skills that require some kind of physical movement, like learning how to ride a bike or drive a car — knows that skills don't come easily. We're not computers. We can't just plug in and know kung fu. It takes a lot of practice and repetition. And if there's no clearly attached value or outcome for you, you're far less likely to evolve, which leads to organizations that stagnate more often than not.

Anne: It really does create that ripple effect in the workplace culture. And when employees see team leaders being hired whose skills weren't really matched to the role correctly, that turnover creates a lack of confidence in leadership from the rest of the employees. Would you say that would also be an impact?

Tigran Sloyan: Yes, and it creates a culture. I once heard a saying that I strongly believe in: culture is not created by the posters people put on the walls. Culture is created by who organizations hire, fire, and promote.

And if hiring, firing, and promotions are not based on merit — not based on skills — you start to create an organization where other things become more important, such as political connections or being good at managing up. It is almost culture-forming if you are not using skills as your driving element for how work gets done and who is capable of doing it.

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Anne: So Tigran, I want to dive into some SHRM research here. SHRM's framework for HR excellence called HRX helps HR create value for an organization by measuring the maturity of HR teams across their key areas of work. One of those HRX dimensions is talent optimization — essentially how organizations develop, engage, and get the most out of their people.

The SHRM HRX research actually found 23% of HR teams operate at a low maturity level when it comes to talent management, and only 7% rank at high maturity. So Tigran, why do you think these specific muscles are currently underdeveloped?

Tigran Sloyan: I think this came from Japanese factories, but it has become a core business principle: you can't optimize what you can't measure. It's a well-known concept in factory production, but it holds true broadly. When you don't know whether the actions you're taking are moving things in direction A or direction B, you're shooting in the dark. If you're trying to optimize something, you have to have a way of measuring it.

I think fundamentally why organizations are not very good at this is that they just don't have a proper way of measuring skills. There have been some attempts — for example, what people sometimes call skills inference, where you look at a corpus of data in the organization and say, "We see that some people work in this tool, some people work in that tool, and these tools tend to be connected to these kinds of skills, so we're going to infer that relationship." That's been one of the bigger innovations in this space.

But fundamentally, that is still a very unreliable measure. Inferring that I know project management because I use Jira — there's some relationship there, but the link itself is very, very weak.

Also, if you're going to measure skills, you can't just measure having or not having them. You have to measure the degree of competency. I often joke that if I was applying to be an NBA player, I'd put on my resume that I can shoot a basketball — and so would Michael Jordan and Steph Curry. The level of skill there is very, very different.

People sometimes write down a skill profile without mentioning degree of competency, and that says absolutely nothing. If I say "I know project management," I could have spent 10 minutes reading an article about it, or I could have been doing it for my entire career.

Anne: I love your analogies in this episode — they paint such a clear picture. I loved the Steph Curry comparison. So we touched on AI earlier, and it really is woven into everything we're talking about today. SHRM's research report "The Skills-First Movement: Redefining How Organizations Hire and Grow" found that more than 80% of HR pros, executives, supervisors, and workers all agreed AI will change which skills are valued over just the next three years. How do you see AI already impacting skill spotting, and how do you see that evolving over the next couple of years?

Tigran Sloyan: There are a few elements here. Let's start with AI impacting jobs, and then from there we can get into how that impacts skill spotting.

Let's start with jobs. If you asked 10 different people, even practitioners, "What is a job?" you'd likely hear 10 different definitions. And if you can't define something, how do we talk about it? Fundamentally, jobs are a process of turning certain inputs into certain outputs, and this is true regardless of the job. People don't usually think about it that way — they say, "A job is what I do to get paid," or "A job is what I get hired to do." But that is not a definition; that is a relationship.

If you think about it in terms of inputs and outputs — a software engineer, for example, usually starts with some requirements or certain product issues and delivers product features, fixes, or value to the end customer. The same could be said about sales. A salesperson starts with a product or a service, and the output is revenue. You can name any job: there is something given to you as a starting point, and there is something you're expected to deliver.

Why does thinking about inputs and outputs matter? We've talked about how skills are psychological attributes to perform work-related tasks. These are the tasks that take the input to that output. You have to define the inputs and outputs in order to define the job, so that you can say, "These are the things somebody has to do to go from this input to this output."

What does that have to do with AI? When we say jobs are changing, here's what's interesting — the inputs and outputs are not really changing. Think about data science. What are the inputs? Usually a lot of data. And the expected outputs are insights, analyses, and dashboards. Now, in the world of AI, do we expect something different from data scientists? We don't.

What is changing is what sorts of tasks people complete — or are expected to complete — to go from that input to that output. Before generative AI (GenAI), a data scientist spent probably entire weeks just writing queries and writing code by hand to analyze, understand, and visualize data. Now, generative AI (GenAI) is very good at writing SQL and visualization code, so you don't need to do those tasks anymore.

You still aim to deliver the same output, but what has become ever more important is how deeply you can understand the requirements. If you don't fully understand the requirements, your output is going to end up being wrong because you misunderstood what you were even being asked. The fundamental shift is that the outputs we expect from jobs are still basically the same — and maybe we expect more, because now some of the more mundane tasks are handled automatically. But the way you complete tasks is fundamentally changing, which means what sorts of skills are required to do it successfully is changing too.

Anne: I don't think I've had anybody explain it like that before. I love it. Thank you for breaking that down. Now, how is AI impacting skill spotting? I think that's the part two, right?

Tigran Sloyan: That's part two. Historically, there are only two ways you can identify if somebody has the skills or not: you either have to watch them do the job for real, or you have to watch them do it in a simulation. Think about flight simulation — if I want to figure out if a pilot can fly a plane, I have to either watch them fly one or watch them do it in a simulation. When you're hiring, you really want to put them in a simulation because you don't want to put them in a plane and find out they couldn't fly it.

When someone is already on the job and you're trying to understand where they're growing and how their skill sets are evolving, it is easier to look at the job being done and assess how well they're doing it and how it's changing. Historically, doing this was nearly impossible.

Because work on a day-to-day basis is so chaotic and so complex, the only way you could look at somebody doing the job and figure out what skills they have was to hire an army of consultant experts to come in, break it all apart, and figure out who did what, how their skills were applied, and what sort of rubric to use to analyze and evaluate it. This has been done by certain organizations for very mission-critical projects, usually at a leadership level, but never at an organizational scale — because it is slow, impractical, and insanely expensive.

Now, what agentic AI is doing is making it possible to do this at a very large scale through AI agents, and not through hiring an army of consultants.

Anne: I love the examples you brought up — they really help break it down in simpler terms. So I want to dive into what our audience can actually start doing today. We've discussed the problem, so now what? I want to hit on three different groups: the HR professional, team leaders, and those job seekers — like the people you were trying to get into Google whose resumes weren't being prioritized by recruiters — because everyone has a role to play here.

Let's start with the HR professional. If someone wants to build a real skill spotting practice — one that feeds genuine internal mobility — what's the first move they can make this week, and what are some tools they could actually start using?

Tigran Sloyan: As you might guess from what I've described, it all starts from measurement. You can go and build an entire castle of trying to create a skills first organization, but it will be a house of cards if it's built on a foundation where skills are not quantified. Without quantifying skills, the whole thing is going to collapse.

The most fundamental things you can start with are clear definitions and then measurement. Once you have clear definitions of the job and of the skills and can then measure them, and once that foundation is solid, whatever you build on top of it will actually have a chance of standing for the long haul.

When it comes to tools, obviously I'm going to be biased and say go look at CodeSignal. But generally speaking, any product that actually helps you fundamentally define and measure skills is going to put you miles ahead of everybody else in this industry.

Anne: Amazing. Thank you. Now, we talked about the concept of being able to see workers day in and day out, watch them do the work they're doing, and recognize how each of them has different skills that could apply to different areas of the organization. And the people who are seeing that are those team managers and team leads.

So what are some ways these managers can try to unearth those hidden skills on their team, and try to get leadership to understand there's a reason to look internally for promotional opportunities, lateral moves, or even an open opportunity within the organization?

Tigran Sloyan: Absolutely. I will sound like a broken record, but it is still true — they have to understand the definition of the job and the measurement of the skills, and have a clear scale for evaluations, because even that often breaks down.

But the other thing I'll mention is that when it comes to individuals or smaller teams, the ability to build skills has never been greater than it is today, again thanks to AI. Historically, what learning and building skills looked like was essentially watching a video — that's been the best-in-class in educational technology sometimes. But we talked about learning how to ride a bike or drive a car. Imagine if somebody showed you a video of someone else riding a bike and said, "You got that, right? Now hop on the bike."

People often laugh at this example, but it's interesting that psychologically, when it comes to knowledge work — because it is a little more theoretical — we think this can work. But when it comes to something done in the physical world, it's literally obvious that it's impossible.

These skills function the same way in our minds. There is no difference between being a data scientist or a journalist and learning how to drive a car — these are fundamentally the same biological and psychological processes that happen in our brains. That means practice is truly the only way to build skills. Practice, feedback, practice, feedback.

Everyone knows in sports that the way you get good is through practice sessions, drills, and more practice. If someone said, "We're going to change how people build skills in sports — you're just going to watch a lot of videos and then go play, no practice" — that's just crazy. I think a few more years from now we'll come to realize that even at work, and for work-related skills, the same is true. Without those practice drills and continuous feedback, you wouldn't really be expected to play the real game.

Anne: And it's important for those team leaders to encourage their employees to upskill and reskill, and to practice, like you said.

Tigran Sloyan: More than ever. Because leaders know and they see that jobs are changing. And as jobs are changing — not the outputs, but the expected volume of outputs as well as the tasks that you do — we have to learn a new set of skills. And if we keep doing that the way we used to for the past many decades, we're just never going to keep pace with this rate of change.

Anne: Amazing. And I want to wrap with this because we've talked about how job seekers — those people trying to develop their skills — also play a role in this. If skills are becoming a kind of currency, how does someone first self-identify their own skills, and then make those skills visible to the people making hiring and staffing decisions?

Tigran Sloyan: I would say seek out organizations and products that have embraced the philosophy I'm describing, because judging your own skills is very, very difficult. If you don't know any better, you might think you're phenomenal at something when you're not — or the opposite, honestly. There is a lot of research around gender differences in this area: depending on your gender, you might think you're amazing at something when you're not, or you might think you're not very good at something when you actually are.

We've had examples of that through our skills first hiring platforms where female engineers have said, "I wasn't even going to apply for this job, but then CodeSignal told me I'm actually in the top 10% in this role globally." That gave them the confidence to go interview, and they ended up with multiple offers — which just blows their mind, realizing how much they had underestimated their own skills.

Anne: Amazing. And how would you say those job seekers — those people trying to prove their value beyond the resume — can make sure that hiring teams recognize the skills they know they're matched for?

Tigran Sloyan: Unfortunately, if you're coming from outside, it's hard to change those teams directly. But the truth is that there is a very large and very fast-growing movement of organizations moving toward a skills first hiring approach. And you can tell from the outside just by reading how an organization hires. It will tell you whether they're going to do a resume review that reduces you to keywords, or whether they're actually going to look at your skills through a skills first approach in the hiring process.

So seek out organizations that have embraced that philosophy, because once you're in, you'll actually be surrounded by people who are very competent at their jobs, rather than constantly having to figure out who's actually qualified and who's not.

Anne: And you can feel confident about the workplace culture as well. I love that.

Tigran Sloyan: Exactly.

Anne: Tigran, thank you so much for your amazing examples and concrete strategies. I love the analogies you provided to paint the picture in this episode. Thank you so much for your insights today.

Tigran Sloyan: Thank you for having me, Anne. It was a real pleasure and a fun conversation.

Anne: Such a pleasure.

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