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Why AI-Driven Skills Management Has Taken Center Stage

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As we come to the end of a challenging year fraught with disruption, the context in which HR teams acquire and manage their talent has also been altered. What was once deemed to be an incremental evolution towards the future of work and a change in workplace dynamics, has now shifted through the gears faster than anyone could have imagined.

As this process has accelerated, so has the desire to automatically extract and measure skills when sourcing for opportunities, both externally and internally. Not that skills haven’t always been important, but they have now been shunted into the spotlight as the new currency of talent to adapt to the new market we find ourselves in. To delve deeper into this topic, Avature just held the first in a two-part webinar series analyzing how skills management can be enhanced with AI.

So what is driving this, when the emphasis for so long has been on assessing and matching job experience and education why now is there so much interest in skills?

What Are Skills?

To first answer this question it is important to ascertain what a skill is. According to Deloitte, skills are defined as “the tactical knowledge of expertise needed to achieve work outcomes within a specific context. Skills are specific to a particular function, tool or outcome and they are applied by an individual to accomplish a given task.”

The important element of this definition is the focus on how it needs to be used within a specific context. As mentioned above, this context is changing and subsequently so are skills. This makes it more important for organizations to adapt to the new demands of the opportunities they are looking to fill. New technology, innovations, channels of communication and methods of working only fuel the need to look at more than just education and experience.

On top of technical skill sets, there is also an increased focus on enduring skills which are seen as integral to a candidate’s development within a function, organization or market. Abilities such as problem solving, reasoning, negotiation and the capacity to learn new skills are now on the top of the wish list of what HR teams would like to be able to identify and measure in external candidates and employees looking for an internal move.

How Technology Is Changing Skills

An undeniable catalyst for this change is the effect of technology. Thinking of the role of a marketer, what skills would they need now that they wouldn’t have 10 or even five years ago. The tech skill sets needed in today’s market are not necessarily lodged in their education or even necessarily in their experience so have a shorter shelf life. This makes it important for skills to be brought into play to give a broader picture of whether that candidate will be able to hit the ground running or be out of their depth when starting a new role.

This technology has also changed the candidates’ expectations of a working life. New generations no longer want to stay in the same job until the end of their career. They want to learn and move. This means that HR teams are being faced with fewer linear CVs with “classic” career paths and more personalized amalgamations of work experience. This makes it very hard to compare apples with apples and therefore re-focuses the attention back onto the common denominator, skills.

How AI Can Underpin Skills Management

So, as technological advances have increased the challenge of searching for talent, it can also offer the solution. As skills ontologies become more advanced they are able to automate the extraction of skills from job applications, CVs and employee profiles. With the use of semantic AI you are able to associate clusters of the words with the correct skill sets and not just keyword matching which can often lead sourcers down the wrong path.

A good example of this is when looking at food and beverage skills compared with that of food science. Previously a food scientist, whose skill set is chemistry-based would often be recommended and matched with opportunities in the hospitality industry as the skills connection was confined and wouldn’t associate with terms in the correct sector. But as semantic search has evolved, clusters of terms start to emerge around different disciplines which allows a greater level of accuracy when extracting the skills of sourced candidates or internal applicants.

The Importance of AI-Driven Skills Management

Where this has been particularly useful is for internal mobility and the creation of talent marketplaces. Talent marketplaces being defined as “systems, digital platforms and virtual places where organizations provide, and workers find the opportunities most relevant to their mutual benefit and success.” The extraction of skills with the help of AI can be leveraged to create accurate opportunity recommendations for employees, allow for more accurate skills gap analysis and offer tailored career paths to map out an employee’s future at your company.

The essence of a marketplace is that it is dynamic and that it serves as inspiration for employees and hiring managers alike. Allowing automation to do its work to create and maintain this momentum fosters engagement in the IM program by offering a consumer-like experience. The alternative is an HR team manually sending out broad lists of opportunities to employees which is not only time consuming but also less targeted and effective.

This is just one area of the talent lifecycle where the harmony between AI and skills management can be applied. It can also be incorporated into sourcing, hiring processes, onboarding, performance management and learning and development where profiles can be enriched by more accurate skills data.

Looking Forward, Skills and AI Are Just One Piece of the Puzzle

Although accessing and measuring skills with AI are hot topics right now, it is important to remember that they only represent one segment of the full employee picture. This means, accurately assessing someone’s skills is a useful tool for TA and TM processes but is not the answer to all your woes. Having a platform that can draw data from other areas of the talent lifecycle will always give you a fuller picture. This can be in the form of integrating a skills validation process to encourage the uploading of certificates or projects, drawing from performance reviews for real time evaluations on employee’s abilities or adding in career aspirations after manager check-ins. The right technology, plus a skills model, can take the talent game to the next level, enabling AI to carry out the arduous tasks and highlighting the candidate skill sets you need while leaving the recruiters to focus on value-add activities that can build your employer brand.

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