Beyond the buzzword: Why “Adjacency” isn’t enough to fix your skills inventory

If you’re paying attention to the HR tech landscape, you can already feel the shift. By 2026, “Skills Adjacency” is going to be the industry’s favorite buzzword. You’ll hear endless pitches about how it’s the magic bullet for talent mobility and uncovering hidden potential.

But after years of helping companies build and manage complex skill architectures, I need to share a hard truth: Adjacency is just one leg of a three-legged stool.

If you chase Adjacency without the other two foundational pillars—Taxonomy and Ontology—your skills strategy will collapse. To build a skills inventory that actually works, you need to understand that these three properties solve completely different problems. You cannot swap one for the other.

Here is how I explain these properties to organizations that want to move beyond the hype.

Taxonomy: The backbone of reporting

Taxonomy is your classification system. It’s the folders, the buckets, the hierarchy. Its primary function is aggregation to ensure transparency.

When we dump 5,000 skill tags into a bucket without structure, we create chaos. Taxonomy brings order to that chaos.

The most effective way to understand this is through the animal kingdom. Biological classification works because it has a standardized depth. Whether you are looking at a sponge or a tiger, the classification rules are the same:

• Kingdom: Animalia
• Class: Aves (Birds)
• Order: Accipitriformes
• Species: White-tailed Eagle

The business translation

In the corporate world, we apply this exact same logic to skills. Different stakeholders need different levels of granularity. The CEO needs the big picture; the employee needs the specific technical term.

Here is what a healthy 4-level taxonomy looks like for a specific HR skill:

• Level 1 (Area): Recursos Humanos
• Level 2 (Category): Organizational Design
• Level 3 (Group): Team Structures
• Level 4 (Skill): Tribe Structures

The “golden rule” of depth One critical lesson we learned at Skillpanel is that standardized depth is non-negotiable. We use a strict 4-level hierarchy.

Why? Because if your Engineering team uses a 9-level deep structure and your Marketing team uses 2 levels, you cannot report across the organization. Dynamic depth makes reporting a nightmare. A fixed depth creates a common language that supports everyone from the entry-level specialist to the C-suite.

Ontology: The logic of connection

If Taxonomy is the skeleton, ontology is the connective tissue.

Taxonomy organizes skills into folders; ontology defines the logical, “visible” relationships between them. This isn’t based on guesswork; it’s based on explicit rules and logical requirements.

When we build an ontology, we are answering the question: “What are the rules of this domain?”

• Prerequisites: You cannot learn React until you understand JavaScript. That is a hard rule.
• Replacements: The technology changed. Google Universal Analytics is now deprecated; GA4 is the replacement.
• Similarities: Customer Success is functionally very similar to Account Management.

Why this matters: Ontology acts as a “GPS” for learning paths. When an employee asks, “What should I learn next?”The taxonomy tells them where a skill sits, but ontology maps the logical path to get there. It is critical for optimizing reskilling because it prevents people from jumping into advanced concepts (Level 4) without the foundational prerequisites (Level 3).

Adjacency: The data-driven reality

This is where the confusion usually starts. Adjacency looks similar to ontology, but it solves a completely different problem.

While ontology maps how skills relate conceptually, adjacency reveals how skills relate in practice. It is based on data, co-occurrence, and statistical probability.

Adjacency answers the question: “Which skills tend to hang out together in the real world?”

The “Google Cloud & Agile” Example

Let’s look at a real-world example.

• In your taxonomy, Google Cloud sits under “Technology.”
• In your taxonomy, Agile Methodologies sit under “Project Management.”
• They are in completely different folders.

However, adjacency looks at the data and says: “Hey, 85% of the people who have the Google Cloud skill also have the Agile skill.”

These skills have high adjacency (co-occurrence). This creates a “gravity” between them. It’s not a logical prerequisite. For instance, you don’t need Agile to code in the cloud, but the data shows they are deeply intertwined in modern roles.

Why this matters: Adjacency supports navigation and discovery. It helps you spot trends that your logical ontology might miss. It suggests that if you are hiring a Cloud Architect, you should probably check for Agile experience, even if the job description didn’t explicitly ask for it.

The synthesis

You cannot choose just one.

• Taxonomy gives you the reporting structure to satisfy your stakeholders.
• Ontology gives you the logical paths for valid learning and development.
• Adjacency gives you the real-world context of how skills actually interact.

My advice? Don’t let the 2026 buzzwords distract you. Adjacency is powerful, but only when it’s built on top of a solid Taxonomy and a clear Ontology.