Unleashing Competitive Advantage: The Power of a Skills-led Organisation

In a world that is digitising and automating at an ever-faster pace while also facing into disruption across technological, economic and geopolitical frontiers, workforce skills are not just strategically relevant but existentially important. It's no longer just about job titles and traditional roles; it's about planning and managing workforce comprising a diverse, fluid set of skills and channeling the deployment and development of those skills in the optimal way.

Across our engagements with FTSE100 clients, we find that over half of internal job postings are asking for a skillset which can be filled internally, after some limited reskilling, by someone not currently performing that role. When recruitment is struggling to fill roles externally and compromising on talent, we see this as a golden opportunity to target an often sizable learning spend on a demonstrable return - it just needs robust workforce skills data to achieve. In fact, the opportunity of going "skills-based" across a broad range of KPls - recruitment cost. internal fill rate, regretted attrition, open positions, time-to-hire, learning Rol - cannot be understated

The challenge then comes in creating and managing a new skills data capability to seize this opportunity - and to be honest it remains a developing discipline. Read on for some of our learnings to help you on the way.

Whether in talent acquisition, reward structures, learning initiatives, or business operations—one often neglected treasure is the wealth of skills data already residing within your organisation. In the emerging world, AI is accelerating our ability to transform fragmented data into a dynamic 'skills ecosystem' that can be leveraged to gain competitive advantage. Here's our nudge to kickstart your skills ecosystem thoroughly examine where your skills data currently resides within your systems; there is more than you think.

Chances are, skills data is already scattered across your organisation’s job profiles, resumes, talent & learning profiles, career frameworks, and productivity systems, actively utilised by employees, leaders, and HR – but in an un-managed, incoherent way. You probably have the constituent parts for a skills-linked job architecture (list of skills required to perform jobs) and employee skill inventory (list of skills acquired by employees), and you can unleash some powerful AI on these constituent parts to take the pain out of bringing the data under control.

• Skills Taxonomy

A list of all the skills required for all jobs across the organisation, organised into a hierarchical structure. This results in a comprehensive list of skills that can be rolled up into larger ‘clusters’ of skills for easier analysis at the org level. 

• Job: Skill Mappings

The skills required and/or currently performed by each job profile. Using AI, skills are inferred from job profile names, job descriptions, and market data. 

• Skill Inventory

Each employee’s personal skills, usually validated by the employee themselves. Most employees should have overlapping skills with their job profiles; however, they may not have all the skills required for their job (which can help identify upskilling requirements) and they may have additional skills not required for their job profile, but gained over the course of their career. 

So, you’re sold on the case for skills and you’re ready to embark on the journey, you may then ask what’s next? The good news is that you’re very likely to have much of the input data you already need, the technology exists today to do much of the heavy lifting, and you’re not a first mover so some of the hard lessons have been learned already.

We’ve compiled some of those hard lessons and success stories from across the industry to help you get on your way.

3 Do’s:

If we consider some of the most powerful use cases for skills

1. Skills-based hiring to increase candidate pools by removing the need for experience in a particular job
2. Personalised learning plans to close gaps between learners’ current skill profile and those required for their current or target role
3. Understanding of what skills best drive business performance
4. Understanding the gaps between the available skills of today and the required skills of tomorrow

They all require a view of the relationship between the skills required to perform a role (job:skill architecture) and the skills employees have (inventory). These are the key pieces of the puzzle you need to demonstrate value to the business – focus on them. 

One of the hardest success factors in your skills journey is winning the attention of senior stakeholders in the business, co-creating your skills solution with them, and bringing them along on the journey. HR projects are prone to fall by the wayside because they are too disconnected from where the money is made. Find the most senior business leader you can, persuade them of the business case, and give them create content documenting the journey to play into senior forums.

In turn, this conversation will mean that you’re tailoring your solution to solve a real problem as well as accessing relevant skills data from the business. Once you’re ready to finish proving skills concepts and move skills-based capability into production, it’s most likely the business that will need to pay.

Zooming into HR, skills transformation is naturally cross discipline and precursors a future state for HR which has broken down some of the boundaries that exist today. Ensuring your skills solution is designed and implemented with involvement across the big stakeholders in HR will in turn ensure the awareness and features exist for it to form the cornerstone of functional strategy:

• Talent will own the Talent Strategy and have a particular interest in internal mobility, maybe through a Talent Marketplace, which will be a key beneficiary of (and contributor to) a skills architecture and inventory
• Learning is often a very large cost centre within HR and stands to benefit hugely by making learning more targeted, more personalised, and more strategic – they also may have learning profile data you want to include in scope for your skills inventory
• Recruitment is often a pain point from a process perspective and this isn’t helped by struggles with finding good candidates for key competitive roles such as in digital
• Analytics as a relatively new player to the HR landscape, skills data can be a powerful use case for a People Analytics team to demonstrate their value and capability to both the business and the broader HR team
• Strategic workforce planning will be one of the first players to unlock the value of skills data and is a great use case to demonstrate the transformative power of skills data across the enterprise, or in areas with high criticality
• Technology is a critical enabler to your skills strategy, and should be brought along the implementation journey to ensure configuration with existing systems is optimised

3 Don’ts:

Many of the key use cases for skills data do not need a perfect, multi-layer skills taxonomy. There is a common misconception that the taxonomy is the foundational first step in the skills journey, and many efforts fail in the attempt to achieve unanimous agreement. Instead, navigate this journey with a strategic focus, understanding that simplicity and adaptability often pave the way for successful skills-led initiatives. By embracing flexibility and avoiding unnecessary intricacies, organisations can foster a more agile and effective approach to skill development.

Transitioning to a skills-based organisation requires embracing essential lessons. Rather than being solely platform-led, focus on foundational elements. Don't hastily invest in shiny tools without an-depth understanding of their long-term impact. By establishing a robust foundation first, organisations can make informed decisions about platform acquisitions. This strategic approach ensures that the organisation is well-equipped for success, with a clear understanding of how platforms contribute to the overall skills-led journey.

To avoid overwhelming tasks, focus on a specific business area. Start with a small pilot where you can create demonstrable value and let the internal demand for your skills data organically grow. Define clear success criteria from the beginning, and continuously track progress against measurable benchmarks. Through this journey, adaptability is key—be ready to refine, expand, or pivot strategies based on insights. This iterative process ensures efficiency and increases the likelihood of successfully becoming skill-led.

The marketplace for skills vendors is moving quickly, so it’s imperative that your organisation prioritises building a solid foundation first, and then keeping an eye on suitable technology. A strong foundation to your skills data will enable your organisation to flex and mature alongside the market, unlocking the best value possible from evolving tech solutions. We also encourage you to begin your skills journey with defining well-designed success criteria, and then embedding genuine “Go/No Go’s” throughout the build phase that tie back to your pre-determined metrics.