Skills-first approach: How cutting-edge skills data can help build an adaptable, resilient workforce

We have seen a lot of change and uncertainty in the world of work in the last few years: COVID-19, the Great Resignation, rising inflation and cost of living, and generative AI, to name just a few. This has supercharged transformation projects driven by remote work, automation and digitization, and increasing cost and competitive pressures. The result is an accelerated shift towards a skills-based operating model for talent.

As unemployment rates remain low, salaries get higher and critical projects demand new skill sets, managing the talent life cycle requires a holistic approach; one that allows organizations to demonstrate greater agility and respond to shifting business needs more effectively.

Businesses that move quickly towards the skills-first model will be more competitive and emerge stronger by building a more resilient and adaptable workforce.

A skills-first approach starts with rapid workforce planning, in order to:

A well-defined, skill-based job architecture is a critical stepping stone to effective workforce planning. The problem most organizations face is that they struggle to keep skills data up to date and accessible. For most businesses, this information lives across multiple, disconnected systems and doesn’t update as people develop and add to their skill sets. This is where an AI skills-inference platform can help by creating a clear and consistent skills taxonomy specific to each organization that adapts automatically as the business evolves.

You need a single source of information for your talent teams and broader business: a clear, common language and a place where they can see a snapshot of your workforce’s skills at any given time. Making sure that HR systems such as your applicant tracking system and candidate relationship management follow the same skills taxonomy is key.

Developing a strategy to close skills gaps must include anticipating a future state of demand, as well as modelling internal and external market supply: the skill supply model. By understanding the skills you have and those you need, you can develop more targeted hiring, employee development and internal mobility initiatives.

Building a talent pipeline filled with engaged candidates that recruiters can connect with at any time and having a clear view of their skills is one of the best ways to ensure your business can adapt to rapidly changing talent needs.

Going a step further and using an AI-powered skills platform to create a “skills adjacency map” will show you the proximity of one skill to another, and the actions and costs required to develop them. Now your skill supply model captures current and future skill availability against the axes of time and cost.

From here, an organization can make far more effective decisions on building, buying or borrowing to close the skills gap within the time and budget available.

In a tight (and expensive) labour market, employee retention and internal skill development are more important than ever if you want to build an agile and resilient organization. Creating skill development programmes at scale should involve the following:

Employee development pathways should always be designed to build skills that align with business objectives – but with objectives shifting, you need flexible programmes. Recommendations around learning, work rotations and even new mentors should always be based on the most up-to-date view of the skills gaps you urgently need to address.

Focusing on skills development ensures that the workforce continuously evolves, which is essential in today’s rapidly changing business environment. One of the best ways to encourage this type of development is through new opportunities for on-the-job learning, that is, internal talent mobility and gigs (shorter-term projects).

As well as being an effective way to engage and retain top talent, internal mobility is a key feature of an agile, adaptive, skills-first company. As business needs change, the most efficient way to close skills gaps is to redeploy talent internally – it’s faster and less costly than sourcing a new employee. This is especially true if you have the data at your fingertips and the technology to match people to opportunities, based on the skills required.

With ethical, explainable AI applied to your dynamic skills data, you can build such an engine, where you can also identify those employees that don’t yet have the skills you’re looking for, but have the potential to be upskilled – so they can fill the critical roles that emerge in the future.

With a skills-first approach, you start to build the intelligence you need to make better decisions around talent and create flexible workforce plans.

A skills taxonomy and job architecture for your organization means you can assess skill availability internally, and this should be augmented with insights from the broader market. With the right technology, you can also gather insights like someone’s likelihood to move, or to engage with a job posting.

Discover which are the most critical skills, slice your data with filters (like geography or department), and apply AI to the data to make inferences and get insights, such as which skills are usually paired with certain others, unique pairings of skills, and the number of people with skills vs. needs in your future workforce plan. From here, you can use the intelligence to spot ways to close skills gaps, carry out successful mergers and acquisitions (with a talent integration plan), shape the workforce for expansion or contraction, and prepare your business for full-scale transformation, as required.

A skills first approach to hiring and talent management is essential for organizations seeking to navigate uncertainty and maintain a competitive advantage. By understanding the skills they currently possess, and identifying the skills they need to develop or acquire, organizations can develop more targeted hiring, employee development, and internal mobility initiatives, and ultimately build a more agile and adaptive workforce.