Latest / Career Skills with Fexingo: Hard Skills, Soft Skills, and Future-Proofing Your Career / How to Find Your Skill Adjacencies
Transcript
- Lucas: So about eighteen months ago, a marketing manager at a mid-size consumer goods company realized she was bored. She liked the strategy part of her job — running A/B tests on email campaigns, segmenting customer data, forecasting campaign ROI. But she didn't want to go deeper into marketing. She wanted to go into data analytics. Luna: And I'm guessing she didn't quit her job and go back for a master's degree. Lucas: Exactly. She took a six-month internal rotation into the analytics team. And the reason she got that rotation? She'd built a small dashboard in Tableau for her own campaigns, and she'd already been using SQL to pull customer lists. She wasn't starting from zero — she had what I want to call 'skill adjacencies.' Luna: Skill adjacencies — I like that. So the idea is that your current abilities are closer to a new role than you think, if you know how to map them. Lucas: Right. And this is the angle we haven't really hit yet on the show. We've talked about building a skills portfolio, about stacking skills, about badges. But what about the skills you already have that you're undervaluing? The ones that sit next to the role you want. Luna: So how do you actually find these adjacencies? Is there a framework? Lucas: There is. I call it the Skill Adjacency Matrix. It has two axes: on the vertical, you list your current skills — both hard and soft. On the horizontal, you list the skills required for a target role. Then you look for overlap. Luna: Sounds simple, but I imagine the trick is knowing which skills to put on the vertical axis. Lucas: That's the hard part. Most people only list the obvious ones — 'I know Excel,' 'I can write a press release.' But they forget the meta-skills. The marketing manager I mentioned — she had pattern recognition from analyzing campaign performance. She had stakeholder management from working with the sales team. Those aren't things you put on a resume, but they're directly relevant to analytics. Luna: So you're saying soft skills count as adjacencies too. Lucas: Absolutely. And there's research to back this up. A 2023 LinkedIn study found that nearly 70 percent of career transitions happen into roles where the person had at least 50 percent overlapping skills. So half the battle is just recognizing the overlap. Luna: But what about someone who has a very specialized skill set? Like a nurse who wants to move into health-tech product management. Is that even possible? Lucas: That's a perfect example. I read about a registered nurse who did exactly that. She had clinical knowledge, empathy, and experience with electronic health records. Those are adjacencies to product management — understanding user pain points, prioritizing features, managing cross-functional teams. She took a six-week online course on product management, then applied for a role at a health-tech startup. She got it. Luna: So the jump was from nurse to product manager in six weeks? That's fast. Lucas: It sounds fast, but she'd been a nurse for eight years. She wasn't starting cold. The course just gave her the vocabulary and the framework. The real value was her clinical experience — no other product manager on that team had actually used the software as a nurse. Luna: That's a powerful point. So the adjacency isn't just technical skills — it's domain expertise. Lucas: Exactly. And that's something you can't learn in a bootcamp. It takes years to build. So if you're thinking about a career change, the first question shouldn't be 'What new skills do I need?' It should be 'What do I already know that this new role needs?' Luna: Okay, but let me play devil's advocate. If everyone starts focusing on adjacencies, doesn't that lead to career hopping without depth? People jumping around every two years, never becoming experts at anything. Lucas: It's a fair concern. But I'd argue that adjacencies are actually the opposite of shallow hopping. When you move into an adjacent role, you're building on your existing expertise, not abandoning it. The marketing manager who went into analytics — she still uses her marketing knowledge every day. She just applies it differently. Luna: So it's more like a spiral than a ladder. You're building breadth while maintaining depth. Lucas: That's a great way to put it. And there's a useful rule of thumb called the 70-20-10 model for skill development. Seventy percent of learning comes from on-the-job experience, twenty percent from exposure to others, and ten percent from formal training. Adjacencies thrive in that seventy percent — you learn by doing, but you're doing something slightly new. Luna: So how do listeners actually map their own adjacencies? Give us a concrete exercise. Lucas: Start by listing every skill you've used in the last year — and I mean every single one. Include things like 'negotiating with vendors,' 'analyzing survey data,' 'giving presentations.' Then look up a job description for a role you're curious about. Copy the requirements into a second list. Then draw lines between matching skills. Luna: And I imagine some matches won't be obvious. Like 'managing patient care' might match 'managing product roadmaps' in terms of prioritization. Lucas: Exactly. The key is to abstract the skill. Don't think 'I titrated medications.' Think 'I followed a protocol with conditional logic.' That maps directly to the logic of A/B testing or workflow automation. It's a mindset shift. Luna: There's also the question of how many adjacencies you need. Is there a magic number? Lucas: Not a magic number, but research from the Burning Glass Institute suggests that if you have at least four or five strong adjacencies, your odds of a successful transition go up significantly. And those adjacencies don't all have to be technical. One could be 'fast learner,' another could be 'domain knowledge.' Luna: What about tools? Are there any platforms that help with this mapping? Lucas: Yes. The US Department of Labor's O*NET database is fantastic. You can search any occupation and see a detailed breakdown of skills, abilities, and work activities. Then you can compare two occupations side by side. LinkedIn's Skills section also shows you how your skills relate to other roles. And there's a tool called SkillSurvey that some career coaches use. Luna: So O*NET is free? Lucas: Totally free. It's one of the most underused career resources out there. You can literally type in 'marketing manager' and 'data analyst' and see a percentage of skill overlap. It's eye-opening. Luna: I want to go back to something you mentioned earlier — the idea that people undervalue their own skills. Why do you think that happens? Lucas: Partly it's humility. Partly it's that we take our own capabilities for granted. If you've been negotiating contracts for five years, it feels like 'just part of the job.' But to someone who's never done it, that's a huge skill. There's also the impostor syndrome factor — you assume everyone else can do what you do. Luna: So the exercise of listing skills is partly a confidence builder. Lucas: Absolutely. And I'd recommend getting a second opinion. Ask a colleague or a mentor to list what they see as your top skills. You'll be surprised. I did this exercise with a friend who worked in HR — she said her biggest skill was 'reading a room.' She never would have put that on a resume, but it's incredibly valuable for roles like change management or consulting. Luna: That's a soft skill adjacency. So it's not just about hard skills like SQL or Python. Lucas: Not at all. In fact, some of the most powerful adjacencies are soft skills. Communication, empathy, adaptability — these transfer across almost any role. The World Economic Forum's Future of Jobs Report consistently ranks these among the top skills for 2025 and beyond. So if you have them, you're already ahead. Luna: Let's talk about the flip side. Are there any risks to focusing too much on adjacencies? Lucas: The main risk is that you might try to force a connection that isn't there. Just because you know how to use Excel doesn't mean you're ready to be a data engineer. You need to be honest about the gap. The adjacency gives you a head start, but there's still a learning curve. Luna: So it's about finding the intersection of 'I can do this' and 'I want to do this.' Lucas: Exactly. And that's where the motivation comes from. When you can see a clear path from where you are to where you want to be, the work doesn't feel like a slog. It feels like progress. Luna: I think we've given listeners a lot to work with. I'm going to try that O*NET exercise this weekend. Lucas: Do it. And when you find those adjacencies, you'll realize the next step in your career might be closer than you thought.