Latest / Future of Work Tech with Fexingo: Remote Tools, AI Productivity, and Workplace Software / How Employee Skill Data Is Becoming the New Oil
Transcript
- Lucas: So there's a quiet transformation happening inside large companies, and it's not about return to office or four-day weeks. It's about how employers are systematically cataloging every skill their employees have — and using that data to redeploy talent internally like a stock exchange trades shares. Luna: I've heard the term 'talent marketplace' thrown around. Is that the same thing? Lucas: Exactly. But let's be specific. Accenture has something they call 'MyScheduling' — it's an internal platform that tracks the skills, certifications, and project experience of over seven hundred thousand employees. When a new client engagement comes in, a manager can search the entire global workforce for someone who speaks Japanese, has SAP implementation experience, and is available next month. It matches internally before they even consider outside hiring. Luna: That sounds incredibly efficient. But also — a little Big Brother-ish. Are employees opting in, or is this data pulled from performance reviews and Slack messages? Lucas: That's the tension at the heart of this whole trend. The best implementations are opt-in and employee-driven. You build your own profile, you flag your aspirations — 'I want to move from marketing into product management' — and the algorithm suggests projects or mentors. Unilever does this with a platform called 'Flexible Work' where employees can sign up for short-term 'gigs' outside their usual role. It's designed to surface hidden talent. Luna: Right, so it's less about surveillance and more about opportunity. But the data itself — who owns it? If I list that I'm learning Python on weekends, does the company now have a record that could be used against me in a layoff? Lucas: That's the question every HR tech vendor is wrestling with. And the answer partly depends on how the system is governed. Some companies make skill data visible only to the employee and their manager unless the employee opts to share it more broadly. Others aggregate everything into a central HR analytics database. The difference between a tool that empowers you and a tool that monitors you is often just a privacy toggle. Luna: I remember reading that Microsoft's Viva Insights tool faced pushback because managers could see how much time employees spent in meetings. There's a trust dimension here. Lucas: Exactly. And the companies that get it right are the ones that decouple skill data from performance evaluation. If your skill profile is only used for development and internal mobility — not for compensation or layoff decisions — employees are far more willing to participate. Deloitte's research found that organizations with mature talent marketplace programs see a thirty to forty percent increase in internal mobility. Luna: That's a huge number. Especially when you consider the cost of external hiring — recruiters, onboarding, lost productivity. Lucas: Yeah, the economics are strong. And this isn't just for giant consultancies. There are now platforms like Gloat, Fuel50, and even LinkedIn's internal talent marketplace product that mid-size companies can adopt. The barrier to entry is dropping fast. Luna: So if I'm a VP of HR at a five-hundred-person company, what's the first step? Do I need to build a giant skills taxonomy? Lucas: You don't need to boil the ocean. Most platforms start with a lightweight skills ontology — maybe a few hundred standard competencies — and then let employees tag themselves. The AI then learns from project histories and peer endorsements to fill in gaps. The key is to start with a specific use case. Say, 'We want to improve retention among mid-level engineers' — so you build a talent marketplace pilot for that one group. Luna: That makes sense. But I wonder about the cultural shift. A lot of managers are used to hoarding their best people. If an algorithm starts pulling your star analyst into another team's project, that creates friction. Lucas: It does. That's actually the biggest implementation hurdle, not the technology. You have to change manager incentives. Some companies tie a portion of a manager's bonus to how many of their people get promoted or move into new roles. It shifts the mindset from 'I own this person's time' to 'I develop this person's career.' Luna: That's a pretty fundamental shift in management philosophy. And I can see why a lot of firms would talk about it but not actually do it. Lucas: Right. The talk to action gap is real. But the companies that have done it — like Unilever, which now fills about forty percent of roles internally through its platform — are seeing measurable impact on retention and time to productivity. Luna: And this also ties into the whole skills-based organization idea that's been floating around. Instead of organizing by job title, you organize by what people can actually do. Lucas: Exactly. And that's where the data becomes really powerful. Once you have a dynamic map of your workforce's capabilities, you can spot emerging skill gaps before they become crises. You see that only five percent of your workforce has any AI literacy — well, now you know where to invest in training. Luna: That kind of foresight is something most companies don't have today. They rely on annual surveys or exit interviews, which are always retrospective. Lucas: Precisely. And this is where the conversation gets really interesting for smaller companies. You don't need a massive platform. Even a simple internal directory where people list three skills they want to develop, and a manager who checks it monthly — that's already a step forward. Luna: So the tech is almost secondary to the culture of transparency and development. But the tech does make it scalable. Lucas: It does. And the data generated — anonymized and aggregated — becomes a strategic asset. You can model scenarios: 'If we lose twenty percent of our senior engineers, what's the fastest way to backfill from within?' That's talent planning on a whole new level. Luna: I can see why some people call skill data the new oil. But like oil, it needs to be refined — and handled carefully. Lucas: Yeah, and that's probably the right note to end on. The potential is enormous, but the ethics have to be baked in from the start. If the data is used to develop people, it's a win. If it's used to control them, it backfires — just like employee monitoring software, which we talked about a few episodes ago. Luna: Quick honest thing — a handful of listeners chip in monthly through buy me a coffee dot com slash fexingo, and that's literally what funds making this many of these episodes ad-free. If today's tech conversation gave you something usable, that's the way to keep it going. Lucas: Yeah, and we really mean it — no ads, no sponsors, just listener support. It keeps the conversation honest. Luna: Exactly. So back to skill data — one thing I'm curious about: are there any startups building this for small businesses on a budget? Lucas: Yes, there's a wave of affordable options. Companies like Hone, BetterUp, and even some CRM platforms are adding lightweight skills-mapping modules. You can get started for under a few thousand dollars a year. The biggest cost is actually the time to get employees to fill out their profiles — but if you tie it to their development goals, most people are happy to do it. Luna: So the barrier is more behavioral than financial. That's encouraging. Lucas: I think so. And once you have that data, you can start having much smarter conversations about career paths. Instead of asking 'What job do you want next?' you ask 'What skills do you want to build?' That subtle shift changes everything.