Today’s workplace is experiencing a serious skills gap that experts are predicting will only worsen. The combination of veteran workers retiring and new workers entering the workforce unprepared has organizations scrambling to find new ways to close the widening gap between open positions and qualified employees. But as companies are realizing that the learning and development of their employee base requires more individualization to truly be valuable, solutions that leverage big data for more targeted and adaptive learning at enterprise scale will play a major role.
The gap that’s been created has led to a learning crisis forcing a fundamental shift in the way learning solutions are now delivered and consumed. Because of this shift – from a talent crisis to a learning crisis – we’ve arrived at what we call the Learning Age, in which success, velocity and market leadership will be defined by a variety of factors, but will ultimately boil down to how well organizations are able to develop employees to their full potential through learning. A critical factor in making this happen is to create an adaptive learning solution that leverages past experiences and best learning practices to create an experience that is expressly catered to each individual situation. By using real-world data to better understand the learning experience and behavioral patterns of all types of learners, we can continually adapt and improve that system over time.
A recent live research pilot with two cohorts of customers explored how data-driven learning can impact employee engagement and development. The results demonstrated the measurable impact of using data-backed intelligence to cater recommended learning resources to an individual’s needs and skill gaps. By testing purpose-built algorithms in a framework powered by millions of learners across tens of thousands of learning assets, results revealed:
- 84 percent of users stated that one or more recommendations made by big data-backed algorithms were relevant to them
- 128 percent improvement in user engagement with learning assets compared to the baseline
Forward-looking organizations that commit to getting ahead of the challenges presented by the Learning Age will find that harnessing the concrete data they have, rather than using a cookie cutter approach to learning recommendations, will form the foundation of the next generation of adaptive learning solutions that appeal to an increasingly impatient, overwhelmed employee. Being able to better understand end user behavior with data intelligence and predictive analytics enables organizations to grow and develop their talent, leading to tangible business outcomes and fewer gaps in knowledge and training. The resulting growth in human capital is indispensable for any organization looking to compete in today’s business environment.
It’s widely acknowledged that the skills shortage many organizations are facing around the world is putting great pressure on learning and development professionals to find and develop talent faster and better. Putting the best systems in place to ensure workforces are engaged and given the most valuable learning tools for their role is the only way to fill the skills gaps that exist today and prevent organizations from being crippled by them in the future. Big data, when properly paired with learning technology, is proving it has the potential to change the way we cater our learning solutions at scale to the individual learner and position organizations for ongoing success in an ever-evolving workplace.
