If organisations stay fixated on job titles rather than the underlying skills people actually need, their learning & development programmes end up mis-targeted and under-performing. The shift to a skills-based L&D strategy means identifying which skills matter now and next, designing learning pathways around them, and aligning learning content decisions accordingly. In this blog I’ll sketch the current learning landscape (why skills are top of mind for L&D), then walk you through what a strong skills-based structure looks like in practice.

The learning landscape today: Why skills are top priority

Skills gaps are one of the major L&D issues

• According to the CIPD Learning at Work 2023 survey, 29% of L&D professionals said “addressing the skills gap” is their number one priority.

• That said, only 59% of L&D professionals agreed they can respond with agility to changing skills requirements in their organisation (down from 69% in 2021).

• In the UK more broadly: an analysis found 20% of the workforce could be “significantly under skilled for their jobs by 2030”. That’s around 6.5 million people.

• The UK’s government maintains a collection of “job and skills” data to help map emerging skill mismatches and demand.

  
  

So L&D teams are under real pressure to make sure that what they build maps to skills, not simply to courses for job titles.

Why the traditional job-title model falls short

• Job titles can be vague or outdated - the same title in two teams may demand very different skills.

• Focusing on titles tends to lead to static training packages rather than dynamic, evolving learning pathways.

• Organisations that shift to skills-based models (rather than title-based models) tend to be more agile, better able to respond to changing organisational demands.

• A skills-based model also supports internal mobility: if you map skills rather than just roles, people can see how they move from one skill set to another rather than waiting for a job title to change.

  
  

The implication for L&D leaders in large organisations

If you’re in a large organisation (1,000+ employees) the stakes are especially high. Skills gaps multiply when you have many functions, global or decentralised teams, legacy training tied to roles, and shifting business priorities. A skills-based L&D strategy can help you:

• Align learning with business goals (via skills tied to outcomes)

• Avoid redundant content just because it fits the job title

• Provide more personalised, relevant learning experiences

• Measure impact more clearly (by skill improvement rather than seat-time)

  
  

What a good skills-based L&D structure looks like

Here’s a practical framework you can follow. I’ve broken it into four key building blocks: (1) Skills architecture, (2) Learning pathways, (3) Content & format decisions, (4) Measurement & governance. Each comes with guidance you can adapt.

1. Skills architecture: Establish your skills language

• Define your skill taxonomy - create a consistent list of skills (and levels) that matter to your organisation. Avoid only focusing on job titles. Link each skill to the behaviours and outcomes you care about.

  • For example, tech skills might include data literacy, cloud architecture, AI/automation design; others might be commercial acumen, digital collaboration, resilience in ambiguity.

• Level skills - for each skill determine progression (e.g., Awareness, Practitioner, Expert) so you can map learning accordingly.

• Map skills to roles / functions - but crucially, map roles via skills, not treat roles as the primary filter. Ask: which skills does this role truly need now and next?

• Stakeholder-engage - involve HR, business units, and leaders in defining which skills drive value. According to CIPD many L&D teams still struggle to secure business buy-in for skills-based approaches.

• Maintain and evolve - skill demands shift quickly (especially with technology). As the Deloitte blog puts it: organisations need a skills-hub mindset not a one-off taxonomy.

  
  

2. Learning pathways: From skills to structured journeys

• Identify skill-based pathways - for each key skill or cluster define a learning journey: what does someone need to go from Introduction to Proficient to Advanced?

• Modularise content - design modules by skill (or sub-skill) rather than by job title. This promotes reuse, flexibility and agility.

• Blend formats - include microlearning, peer learning, job-aids, coaching. That way you support the flow of work (more on format in the next section).

• Enable mobility - when you use pathways, you can show employees: You’ve mastered skill A at level 1, you can now pick up pathway B to move sideways or up. This supports retention and internal mobility.

• Link to performance outcomes - each pathway should tie into the business behaviour/outcome you expect (e.g., reduce error rate, improve speed to competence, increase cross-team collaboration). This helps avoid the we just did a course trap.

  
  

3. Content & format decisions: Aligning content to skills (not titles)

• Choose content based on skill level and context:

  • At Awareness level: short micro-modules, job-aids, interactive infographics.

  • At Practitioner level: scenario-based eLearning, peer workshops, coaching shadowing.

  • At Expert level: projects, communities of practice, internal mentoring, challenges.

• Avoid one-size-fits-all for the title: If you still build a course by job title (Sales-Exec 101) you risk misalignment. Instead build by skill “Commercial Mindset – Practitioner) that many roles may take.

• Embed in the flow of work: Use job-aids, prompts, peer-learning moments rather than solely dedicated eLearning events. This supports learner experience and retention.

• Govern wisely: With a skills-based structure you’ll likely need less duplication, better reuse of modules and clearer versioning. This helps manage cost, reduce content ‘sprawl’ and keep tight focus.

• Leverage data and insights: As the CIPD observed, L&D teams still struggle to use data and adapt agilely. Better content decisions come from better insight into skill gaps, learner behaviour and outcome change.

  
  

4. Measurement & governance: Can you show it works?

• Define relevant metrics: Instead of only course-completion or satisfaction, focus on skill-level movement (e.g., % of people moved from Practitioner to Proficient in Data Literacy), functional outcomes (e.g., error rate dropped by 12% in X process), speed to competence, internal mobility rates.

• Dashboard for stakeholders: Present metrics in simple, business-friendly visuals. Avoid dumping raw data. Tell a story: We moved 1200 employees through Skill-Pathway A, average time to competence fell from 90 to 60 days, business error rate dropped by 8%.

• Govern the skill framework: Have a skills-governance forum that maintains skill definitions, validates pathways, tracks versioning. This ensures the taxonomy remains relevant and connected to strategy.

• Govern content investment by skill value: Prioritise developing or refreshing learning modules for skills that link to major business needs (growth, risk, transformation). Skills that are less strategic may get lighter touch or standard off-the-shelf.

• Continuous improvement loop: Use feedback from learners, business units and performance data to refine skills taxonomy, pathways and content. Repeat annually (at minimum).

  
  

Practical example: How it might look in practice

Let’s say you’re in a large multinational manufacturing company. Here’s how you could apply the above:

• Skills architecture: You define key skill clusters such as Digital & Automation Literacy, Operational Excellence, Collaborative Leadership, Customer Insight & Service.

• Learning pathway: For Digital & Automation Literacy, you create three levels:

  1. Awareness – micro-learning on digital tools, automation concepts

  2. Practitioner – scenario-based module + peer discussion + job-aid

  3. Expert – cross-functional project, mentoring, showcase of automation improvement

• Content decision: At Awareness you deliver 15-minute eLearning with simple interactive questions; at Practitioner you run a virtual workshop + micro-simulation; at Expert you roll out an internal hackathon.

• Measurement: You track % completed at each level, time to competency (how long from awareness to practitioner), plus business outcomes like number of automation initiatives launched, reduction in manual hours.

• Governance: Quarterly review of the skill cluster Digital & Automation Literacy to check relevance, review pathway uptake, compare to business priorities (e.g., if AI becomes higher priority then adjust).

  
  

Why this matters commercially

• Better alignment to business strategy: When you build around skills tied to business outcomes (not job titles), you become a strategic partner rather than the training department.

• Improved agility: As business priorities shift (e.g., digital transformation, sustainability, remote/hybrid working) skills-based models enable faster pivoting of learning.

• Increased internal mobility and retention: Employees see clear pathways and how their development links to future roles (not just the next job title).

• Reduced duplication & cost: Reusable modules for skills (rather than bespoke for every job title) reduce content creation overhead.

• Stronger measurement and proof of impact: Skills-based metrics link learning to business performance, making the ROI of L&D clearer.

  
  

FAQs

Q: Do we still care about job titles then?A: Yes - roles and titles matter. But the shift is to use job titles as a navigation point into your skills architecture, rather than as the basis for designing learning. You map from titles to skills, and design learning around the skills.

Q: How many skills should our taxonomy include?A: It depends on the organisation's size and complexity. The key is manageability: start with the most strategic skill clusters (say 8-12) and ensure clarity. You can expand over time. Worse is having 1000 granular skills unmanaged.

Q: What about off-the-shelf training content? Does that still fit?A: Absolutely. Off-the-shelf content can serve lower levels of pathways (Awareness / Practitioner), especially for common skills (e.g., Time Management, Digital Collaboration). The bespoke content is best reserved for your strategic or differentiating skills.

Q: How do we get business buy-in for this shift?A:

• Show with data why job-title-based learning is mis-aligned (e.g., feedback, skill gap results).

• Map at least one business priority (say improving customer experience) to a set of skills and show how a skills pathway can deliver impact.

• Start with a pilot: pick one skill cluster, build a pathway, measure outcomes, and then scale.

Q: How long will it take to shift to a skills-based model?A: Change management matters. You can get a basic skills taxonomy + mapped pathways in 3-6 months (for one domain), but scaling across all business functions and embedding measurement and governance will typically take 12-24 months.