And so, if you're looking to build or lead a winning company today, you either are—or soon will be—wading into the world of skills management. And with it comes a whole new (and frankly confusing) language. What’s a taxonomy? How does it relate to an ontology? Do you need a skills ontology—or is that something your doctor should look at?
At WYWM, we’ve spent the last eight years helping people and organisations navigate this world—not just adopting skills-based approaches but actually making them work. Along the way, we’ve seen how the right mix of clarity, structure, and technology can turn what feels like theory into something practical and powerful. In this article, we’ll share what we’ve learned so you can skip the jargon and focus on what matters: building a more agile, skilled, and opportunity-rich organisation.
A skills taxonomy is just a structured list—a way of grouping and naming skills so everyone’s speaking the same language. Think of it like a library catalogue: it doesn’t tell you how the books connect or what to read next, but it gives you a consistent system to find and file what you’re looking for.
Taxonomies are useful because they bring order. They help with things like job descriptions, learning programs, and strategic workforce planning. Without one, everyone ends up making up their own definitions—and things get messy fast.
Think of it like a library catalogue for your workforce. It tells you:
Taxonomies help you name things consistently. They’re essential when you're trying to:
Popular examples? ESCO, CIPD and O*NET are all widely used taxonomies. They differ in style, but all help you answer the same basic question:
“What skills do we care about, and how do we talk about them clearly?”
Frameworks like ESCO and ANSCO are examples of skill taxonomies. They give you a starting point—but they don’t show how skills relate, evolve, or work together. That’s where ontologies come in…
If a taxonomy is a list, an ontology is a network.
Where taxonomies group skills, ontologies connect them to each other. They help answer the question ‘Is Skill A similar to Skill B?’ and they do this by observing if skill A commonly occurs with the same other skills as skill B. In other words, they are synonymy engines and as such they’re good for understanding if a document, say a resume, is like another document, say a job description.
In short:
Both are useful. Ontologies can take you further.
If taxonomies help you name skills, and ontologies help you connect them, then capability frameworks help you apply them—especially in the context of performance and growth.
A capability framework describes:
These frameworks go beyond just naming a skill. They ask:
Take SFIA (which some people call a taxonomy, but we’d argue it’s really a capability framework or often referred to as a skills framework). It doesn’t just list skills—it defines them at seven levels, with clear behavioural indicators for each.
Capabilities are what let you:
They’re where the rubber hits the road—especially when you want to link skills to real business outcomes.
Here’s the truth: capability frameworks are the best tool we have for defining what a role really requires, assessing people’s readiness, and supporting focused upskilling. They describe not just what a skill is, but what it looks like in action—across levels of proficiency and in real work settings. They offer clarity, structure, and behavioural expectations. That’s gold for anyone trying to match people to roles or design targeted development plans.
But despite their depth and usefulness, capability frameworks were largely overshadowed by ontologies in the first wave of “skills tech.”
Why?
Because early tech hit a limitation: natural language processing (NLP) wasn’t good enough to handle nuance. It needed structure. Ontologies provided that structure. By using graph relationships as synonymy engines, they let systems “rough match” skills between job descriptions and CVs—even if the words weren’t identical. That made ontologies ideal for scale—and they became the backbone of recruitment platforms, internal talent marketplaces, and automated AI-powered talent matching tools.
The catch? That matching is shallow. With these ontology solutions, you can never be certain a person can execute a skill in the way you understand it, and you can never be sure exactly what level of proficiency they have. They get you partway, but not all the way.
Enter large language models (LLMs). With the rise of foundation models and custom RAG (retrieval-augmented generation) solutions, we’re no longer limited to keyword matching or synonym engines. LLMs can now interpret nuance, extract meaning, and evaluate alignment based on intent, not just text similarity.
This changes everything for capability frameworks.
Where older systems struggled to use detailed frameworks (because they couldn’t parse behavioural descriptions or contextual signals), LLMs can now consume a full capability definition—across levels, responsibilities, and context—and compare it to how a person describes their work.
That means we can now:
Instead of broad brushstrokes (“you're a Level 3 developer, aim for Level 4”), we can now say:
“To be ready for this role, you need to show evidence of decision-making under ambiguity, influencing without authority, and integrating customer feedback into architectural decisions.”
That’s specific. That’s actionable. And it changes how people respond.
Here’s the most important outcome: when people clearly understand what’s expected, they’re far more likely to take action, therefore increasing productivity. That’s the real power of capability frameworks—especially when interpreted and personalised through LLMs.
Abstract feedback like “you need to be an expert” leaves people guessing. Granular insights like “you need to demonstrate cross-functional leadership and mentor others on architectural trade-offs” show a clear path.
That shift—from ambiguity to precision—builds self-efficacy.
And self-efficacy is what drives real learning and growth within the workforce:
In other words, technology can now support capability frameworks in the way they were always meant to be used—by helping align workforce skills with business strategy. Empowering individuals to understand where they are, where they’re going, and how to get there—while aligning this journey with organisational goals—is a powerful driver of growth.
We’d be happy to explore what’s possible. Get in touch to discuss how we can support your workforce, capability strategy, and future planning.
