On-demand learning may not yet be a matter of instinct for everyone but the time when it must be is upon us. Continuous on-demand learning is the only way we’ll be able to navigate the future that modern working life demands.
This is not simply an employee issue, employers need to build a culture that expects employees’ to take much more responsibility for their own training and professional development, and that supports them in their efforts to bolster their skills and knowledge.
Enter, emerging technologies
Technologies such as Artificial Intelligence (AI), Machine Learning (ML), voice-assistants and augmented reality are becoming increasingly engrained into our day-to-day lives. In fact, according to a report from Juniper, consumer voice assistants like Alexa, Siri and Google Assistants are approaching ubiquity, and will be present in 55 percent of homes by 2022. But intelligent assistants are about more than ordering takeaways and asking about the weather: the same technologies are starting to transform the way we develop the skills we need to succeed in the increasingly-complex world of work. While the use cases are different from our home-based assistants, the principle is exactly the same: to give us instant, intuitive access to information or training at the precise time and place we need it.
So, what is point-of-need learning and why is it important? This type of learning comes in two very distinct types. The first one is performance support, where learning is directly embedded into the workflow. Performance-adjacent learning, meanwhile, is accessed outside of the workflow. Both have their benefits, but performance-adjacent has the edge when it comes to overall attractiveness for organisations. This is because it is much more cost effective, as well as scalable. As employees are faced with the daunting challenge of mastering an ever-growing number of new systems and technologies to do their job effectively, point-of-need learning will be crucial to businesses’ strategic success.
The future of learning
Technologies such as AI are going to shape the future of learning. A great example is natural language processing – a branch of artificial intelligence that allows computers to process large bodies of human language and interpret and manipulate that data. In terms of learning, this technology can enable precision search putting the learner in the position to skip through content or an online learning module to the relevant information they need. This increases the relevance of the search results to the user delivering the content most meaningful at that point in time - facilitating point-of-need learning.
We’re also seeing augmented reality being used for learning, including at the point-of-need. For example, automaker Mercedes-Benz has used Microsoft’s HoloLens augmented reality system to train employees from across the company including product development and sales. Their application allows Mercedes-Benz employees to examine the inner workings of the automobile without having to deconstruct one. Theoretically this allows the employee to problem solve, reference three dimensional images and more actively engage with the product at the point of need.
The old ways of training are increasingly anachronistic in today’s fast-paced world. Workers don’t have the time to take an hour, a day or longer to attend skills sessions, and we rarely have the time to sift through reams of information to find an answer. Learning solutions that support performance-adjacent learning can resolve this problem by making it easier to access the exact information or solution the learner needs, before getting back to the task in hand.
In a recent O’Reilly study, we examined data from one quarter’s worth of usage (1,622,983 individual learning events across twelve industries) and found that learners were engaged in nonlinear learning behaviour around 42 percent of the time, meaning that almost half of all learning during that time was performance-adjacent. When we talk about nonlinear learning, we refer to learners not progressing in a pre-determined and linear manner through content or learning experiences but rather choosing their own path to make the learning meet an in-the-moment need specific to them. This behaviour may appear as learners jumping in and out of an online platform for short sessions as opposed to traditional and time-consuming engagements with sequential content.
The importance of measurement
Businesses need to ensure that their learning processes are meeting the demands and needs of their employees – not just the skills they require, but also their preferred approach to learning. More often than not, today’s learners (and workers) are overwhelmed and have little time to dedicated to formal learning, are required or opting to work from remote locations, and are being required to learn new things to be successful at an astonishing rate. New technologies are enabling on-demand, in-the-moment learning that not only enables continual upskilling and reskilling but also is more effective as it is more relevant and applied than most traditional methods of training or learning.
With this in mind, the ideas of “time on learning” or “completion data” which are traditional learning and development metrics, are fast becoming obsolete. Yet we’re still seeing organisations reluctant to change their measurement techniques.
Ultimately, for learning and development professionals to implement successful, continuous learning for today’s learners they must ensure that it is embedded at the very core of the workflow. Thanks to developments in technology, such as AI, AR and ML this is not only possible, it is already happening. New metrics will develop to measure the impact of this type of learning and may include better understanding and insight from learning behaviour and correlation to established performance metrics such as promotion rates and retention. As this change is already upon us, it would be prudent for businesses of all types to begin to plan for implementing and encouraging the use of performance adjacent learning solutions as central to their talent strategies.