Insights
2.12.2025
Mikko Kivelä
What is a skills & competencies framework and how to build one for my team?
A practical guide to what a skills and competencies framework is, why it matters, and how to build one step by step for hiring, performance, and growth.
A skills and competencies framework defines the skills, behaviours, and proficiency levels your organisation expects across roles. You build one by mapping key skills, assigning clear levels, and integrating them into hiring, onboarding, performance, and development processes. It creates a shared language for what “good” looks like and enables managers to coach, assess,, and support employees more consistently.
"Skills are becoming the new workplace currency. Organizations that build a dynamic skills architecture gain greater agility, fairer talent decisions, and stronger alignment between people and business needs"
A strong skills framework isn’t just documentation. It is a living process that improves decision-making, accelerates learning, and keeps teams future-ready in fast-moving, AI-native environments. Below, we walk through why skills frameworks matter, the common pitfalls, how to build one step by step, how AI keeps them relevant, and how to know if yours is working.
Why does a skills framework matter?
A skills framework matters because it provides clarity, consistency, and fairness across the organisation. It helps employees understand what is expected at each level, reduces subjectivity in evaluations, and gives managers a structured foundation for coaching and development.
Organisations that adopt structured frameworks see better hiring outcomes, faster ramp-up, improved consistency in performance reviews, and clearer career paths. Research from Mercer, Cedefop, and iMocha highlights that well-designed skills frameworks improve strategic workforce planning, increase organisational agility, and reduce misalignment between business strategy and workforce capabilities:
- Mercer: Using skills frameworks to initiate a skills-powered organization
- Cedefop (AI skills survey summary): Skills empower workers in the AI revolution: A summary of Cedefop’s first AI skills survey
- iMocha: 7 Steps to Build an Effective Skills Framework in 2025
What challenges make skills frameworks hard to build?
Skills frameworks often fail because they become too theoretical, too static, or disconnected from daily work. Many teams struggle because there is no shared skills language, managers interpret proficiency levels differently, or employees receive inconsistent expectations across roles and teams.
Frameworks also become outdated quickly in fast-moving environments. Without clear integration into hiring, onboarding, performance reviews, and development discussions, they remain unused. Manager capability is another barrier: even the best frameworks fail if leaders don’t know how to apply them consistently.
What metrics show that a skills framework is actually working?
A skills framework is working when it leads to clearer hiring decisions, faster onboarding, more consistent performance assessments, and more predictable development paths. Employees should be able to articulate the skills they need to progress, and managers should be able to justify assessments with consistent criteria.
You should also see fewer early hiring mismatches, increased internal mobility, and more explicit conversations during reviews. When skills data starts informing workforce planning and upskilling decisions, you know the framework is creating real operational value.
What tools help maintain a skills framework over time?
Tools that support skills taxonomy design, proficiency mapping, feedback collection, and skills inventory tracking help keep the framework credible and actionable. Skills-matrix and role-mapping tools make gaps visible and support more strategic workforce decisions.
AI-powered tools are increasingly common because they keep frameworks up to date as skills evolve, especially in areas such as AI fluency, digital capabilities, and leadership behaviours. AI can surface emerging skills, analyse performance signals, and help refine proficiency definitions, keeping the framework relevant rather than static.
How do you build a skills framework for your team?
A skills framework becomes impactful when it is practical, specific, and integrated into existing processes. This step-by-step approach aligns with other modern practices, and our performance enablement philosophy.
Step 1: Define purpose and scope
Start by clarifying why you’re building it — hiring clarity, development, internal mobility, or readiness for emerging skills. Begin with a few high-impact roles before expanding.
Step 2: Map current roles and skills
Identify key roles and list required skills across technical, behavioural, leadership, and emerging areas. Use input from high performers and managers to ensure expectations reflect real work rather than assumptions.
Step 3: Define skills and proficiency levels
Describe each skill using clear proficiency levels (e.g. basic, intermediate, advanced, expert). Include observable behaviours and outcomes rather than generic descriptors. Align examples with business impact.
Step 4: Link the framework to hiring, onboarding, and performance
Embed the framework into job descriptions, hiring scorecards, onboarding plans, and performance reviews. This makes skills actionable rather than theoretical.
Step 5: Pilot, communicate, and iterate
Test with one team, collect feedback, refine definitions, and clearly communicate the purpose. Only expand once it demonstrates value and usability.
Step 6: Monitor and evolve
Review the framework every 6–12 months. Update definitions as roles shift, new skills emerge, or AI-related expectations evolve. A skills framework should be dynamic, not static.
How does AI make skills frameworks more effective?
AI helps maintain accuracy, reduce manual work, and highlight patterns humans may miss. It can identify common skills across teams, surface emerging competencies, and analyse real performance signals to keep definitions up to date.
AI also supports managers by generating draft frameworks, suggesting updated proficiency descriptions, and providing relevant examples pulled from real behaviour. Tools like Taito.ai’s Leveling Agent make this easier by generating high-quality drafts quickly and keeping frameworks aligned with evolving capability needs.
What does readiness look like before building your skills framework?
You’re ready to build a skills framework when you have clear roles, documented performance expectations, aligned managers, and a plan to integrate the framework into hiring and performance. You are not ready if roles are unclear or if the framework would live outside of existing processes.
| Area | What “ready” looks like | What “not ready” looks like |
|---|---|---|
| Role clarity | Roles and responsibilities defined | Constant role ambiguity |
| Performance expectations | Basic expectations documented | No shared definition of “good” |
| Manager capability | Managers can assess consistently | Managers unsure how to evaluate |
| Integration plan | Clear plan to use skills in hiring/performance | Framework sits unused |
| Update rhythm | Review every 6–12 months | Framework becomes stale |
What should you read next?
These Taito articles extend the concepts in this piece:
- What to have in place before creating a leveling framework
- When to create a leveling framework in an AI-native company
- How to build a role and leveling framework
FAQ
What is the difference between a skills framework and a competency framework?
A skills framework focuses on specific, observable skills and proficiency levels, while a competency framework often includes broader attributes like behaviours, values, and mindsets. Most organisations combine elements of both, but skills frameworks tend to be more actionable, measurable, and easier to integrate into hiring and performance processes.
How often should a skills framework be updated?
Most teams review their framework every 6–12 months, or when roles meaningfully change. In fast-moving or AI-native environments, updates often happen more frequently as new skills emerge and old ones become less relevant.
Who should own the skills framework inside the company?
Typically, People/HR teams own the structure, while managers and functional leaders own the content for their domains. The most effective frameworks are maintained collaboratively — HR handles governance, teams handle accuracy.
How long does it take to build a skills framework?
A basic framework for a few roles can be built in days or weeks. A cross-company framework usually takes longer, but with AI-supported tools (like Taito’s Leveling Agent) you can generate a high-quality starting point in minutes and refine from there.
Should small startups (<30 people) build a skills framework?
Yes — but only for roles where clarity is needed early. Early frameworks should stay lightweight and evolve frequently rather than aim for full coverage. Start small, test with real usage, and scale as hiring increases.
How detailed should proficiency levels be?
Three to four levels (e.g., basic, intermediate, advanced, expert) are enough for most organisations. The key is using observable behaviours and outcomes at each level, not complex definitions that become hard to apply.
How do you prevent a skills framework from becoming too rigid?
Keep the framework focused on clarity, not bureaucracy, and update it regularly based on real work. Use AI and feedback loops to spot emerging skills so the framework evolves with the organisation.
How does a skills framework support career growth?
It shows employees what skills matter for their role and what progression looks like. When integrated into reviews and development planning, it makes growth fairer, clearer, and more predictable.
How do you link a skills framework to performance reviews?
Use skills and proficiency levels as the backbone for evaluations, calibration, and development conversations. This ensures reviews are grounded in evidence and consistent across managers — not based on personal interpretation.