The pandemic has compounded the urgency with which the workforce has adopted a ‘skills-first’ approach to professional development. Seemingly overnight, it was no longer enough to acknowledge the importance of prioritising skills development without proactively doing something about it. 

The rise of remote work, mass closures, organisational shifts, and phenomena like “the great resignation” or the “she-cession,” have further demonstrated just how quickly the working world can change and force our collective hand to change. 

Trying to match the skill requirements of whatever today’s ‘go to market’ strategy entails, with what incumbent talent can deliver, is an enormous challenge. It leaves massive gaps between what we need people to do and what people are currently capable of doing. 

Letting go of legacy notions of job descriptions
Traditional notions of what someone needs to know or demonstrate in the workplace are usually rooted in their original job description. These duties are usually specific, siloed within a team or department, and relatively unchanging over time. Training for that role, naturally, follows suit. 

But this way of thinking about learning and development is no longer sustainable in a digitally enabled and hybrid working environment.

You may have heard people talk about a ‘VUCA’ business environment before; Volatile, Uncertain, Complex, Ambiguous. The pandemic has taken the idea of what we once thought was VUCA and knocked it into fifth gear.

Businesses are pivoting left and right to adapt their models and catch up to whatever the world throws at them. Hotels as quarantine facilities, restaurants you can’t eat in, banks that don’t use traditional currencies. 

On top of this, a sweeping movement towards the automation of roles and functions, economic volatility, and a truly global marketplace has increased both the intensity of competition and the pace of change.

Individuals are now facing a new seismic shift in understanding what it means to be a part of a rapidly evolving workforce – and wondering where their future lies. 

But as overwhelming as the change can feel, it’s important to remember that in change lies opportunity. Developing skills that take change head-on will determine who thrives in a new landscape. 

The role of AI and machine learning in unlocking skills ‘equity’
Traditionally, understanding which skills are actually useful ‘on-the-job’ has always been a bit of a dark art. Twenty years ago, organisations spent fortunes on a constant cycle of competency mapping and job descriptions, trying to explicitly capture what made each role tick. But this was always doomed to a never-ending cycle of documentation trying to keep pace with reality; things moved too fast then and they move faster now.

AI, and specifically machine learning, can help us to map and understand the jobs people really do and the underlying skills ontologies that underpin the work. By analysing large data sets, companies are becoming increasingly capable of determining the common skills and themes that underpin certain job roles and functions. These sets of skills can adapt and change in real-time, they aren’t a written document like they used to be, but a model that learns and changes as the work evolves. 

Data’s crucial role in identifying organisational strengths
Data plays a crucial role in understanding where your organisational strengths lie. By understanding the skills of your people and mapping them back against the organisation’s strategy, you can create a powerful skills gap analysis that can guide the executive team in their decision making processes. 

An AI-infused analytics  helps businesses understand the value that learning/training is providing in the workplace. Analytics models, supercharged with AI, are being leveraged to recommend content to users based on who they are and where they work. The captured data determines how engaged a learner is in a specific topic or how well they understand that topic.  

If your organisation is woefully short in a skill area that the go-to-market plan called for, that’s a good reason to rethink the strategy. Equally, a deeper dive into the analytics of learning can uncover which tactics help improve time to competency in a given area the fastest. It’s not enough to just know where you are strong or weak as a company; you need to know the levers you can pull to quickly upskill and retrain the workforce without wasting time and energy on initiatives that don’t close the gaps. 

Infusing analytics in learning platforms
When it comes to infusing analytics in learning platforms, simplicity is key. Collating and analysing complex data is challenging for nontechnical users. Organisations shouldn’t need to have a team of data specialists simply to make good use of learning data. 

They have the skills and knowledge to use the insights from their data — they just need to have the data available in a more accessible, simpler-to-use, and easier-to-understand way.

Optimising your ‘competitive edge’
The future is complex and uncertain. But it also presents fresh and exciting opportunities. What we do know is that organisations and individuals alike must remain agile and adaptable if they are to meet tomorrow’s challenges successfully. The best way to do that is through the development of skills that optimise your ‘competitive edge.’ 

This is because a highly skilled workforce is more resilient in the face of change and most equipped to seize the moment when an opportunity presents itself. In turn, learning and development that fosters skills acquisition can no longer be limited to job titles. After all, investing in your skill equity is about what you need to do next, not what you’ve already done.