In today’s rapidly evolving world, we have now reached the point where we are no longer limited by computer resources or data, but only by our own imagination in how these can be applied.
One of the biggest recent developments is machine learning. No longer needing to be programmed, computers are being taught to learn on their own, identifying patterns and trends and even making predictions in a way that humans would be incapable of doing on their own.
Machine learning lets data tell a story, rather than just being a bunch of (albeit useful) figures and numbers.
More importantly, though, how is the rise of machine learning affecting human beings? How can this new area of computer science be applied and used in HR?
The simple answer is machine learning has the potential to make huge inroads into reading human behaviour and transform HR through the application of insight.
Transformation or evolution?
These two words can (mistakenly) be used almost interchangeably but there should be a clear distinction. Evolution is about a gradual change (hopefully for the better) that takes place over an extended period. Transformation is a fundamental change, something much more significant and impactful at the point of time in which it occurs. That’s the difference. This misconception can often be applied to HR. For example, despite recognising its importance, HR is still not properly using the power of data. Far from being experience driven, HR is often still driven by simple statistical tools, meaning it doesn’t have the technical capability to deal with such complexities as humans. Machine learning can change this, helping HR to transform, rather than just evolve, and better respond to the requirements of modern workplace and employees.
Learn like a machine
Perhaps ironically, the area where machine learning could be of most use to HR is human learning. Given the rate of digital progress, all employees need to continuously learn new skills and knowledge to keep up with the pace of change – employees’ development is vital to business success. It is also one of the most powerful retention levers we have, for lack of personal development is one of the main reasons why people leave organisations.
However, everyone thinks and learns differently and we all have different cognitive styles – there is a wide range of research that supports this. While some people like examples, others like definitions, some like text and images, and others prefer interactive videos or listening to presentations. There are auditory, visual and kinesthetic preferences to consider too.
Despite these different styles, employees are too often only offered one type of training or are mandatorily assigned learning content by their managers. With employees now needing to be constantly learning, this approach is simply not fit for purpose in the modern world of work.
Now it’s personal
Employers now need to offer personalised learning, tailoring recommendations based on an employee’s cognitive style to ensure workers will reap the most benefit from their training. The problem? Many employees don’t even know what their cognitive style is themselves. This is one aspect where machine learning can help.
With minimal initial input, an employee’s interactions and engagement with learning and training material can be monitored, reviewed and analysed to reveal an employee’s cognitive style and automatically offer relevant training.
There is also the question of what to learn. While there has been a trend towards enables employees to find their own content, this should also be balanced by providing guidance on what to view next. This is precisely the principal behind Cornerstone’s Content Anytime content subscription service, where the content is personalised Netflix-style. Employees are not only offered a wide breadth of topics and types of content, but they receive recommendations based on their interests, their career path and feedback from other users. Machine learning identifies the best options for each individual, taking the guesswork out of assigning training.
Collaborative filtering can help express users’ cognitive preferences, allowing books, training programmes, videos and other content to be grouped together by cognitive styles, rather than subject matter. This means employees are not only more likely to undertake a wide variety of training, but more importantly, to complete it. Rather than working on assumptions, experimental discovery with machine learning helps create playlists and recommendations.
Once employees know their own cognitive style, it is also far easier for them to look for further content, encouraging employees to seek out new knowledge and training for themselves. Employees can even recommend new content or training to their organisation that isn’t currently available, expanding resources and training options but ensuring that this training will be effectively used, aiding better course catalogue management and helping create engaging curricula.
More than just learning
Machine learning can also mobilise talent. It can help recommend positions that an employee can grow into, where they are likely to succeed and what training will help them get there. This can drive greater engagement and productivity, creating effective career paths across the whole of an organisation. To better help an employee’s development, it can recommend courses to an employee to enable their growth to these higher positions and recommend employees for a course.
Employers are also granted an overview of these recommendations for an employee’s progress, monitoring an employee’s potential and their readiness to take their next desired career step. This all strengthens internal talent pipelines and succession planning, to safeguard against potential skills gaps. In a talent-driven economy, it’s important companies focus on retaining their best talent. This is the kind of technology that can help them do so.
By using machine learning, HR can mitigate the risk of missing the right internal talent for a new role. Instead, it can help create the means and the right environment to foster a culture of continuous learning and development. Data can highlight the untold stories in the workplace that can’t be done on a human scale, but it is machine learning that lets employers unlock this potential. By bringing together machine learning and human learning, we can get the best of both worlds.
This piece was originally published in the January issue of Inside Learning Technologies Magazine.
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