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Jamie Lawrence


Insights Director

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How learner data is going to shake up learning and what HR needs to know

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There is a lot of talk about big data and how it will transform businesses and help them become more responsive to customer needs. The same thinking can be applied to corporate learning and development. To date, HR managers and L&D professionals have approached skills development from either a business need perspective or to meet demand from line managers. Now big data, revealing the way in which individual learners are embracing and using e-learning, is driving and developing more effective workforce learning.

The increasing availability of learner data looks set to change learning and development planning and delivery. Learner data can provide real insight into which strategies and content are working and which aren’t. Analytical tools allow HR managers and L&D professionals to respond to individual learners much faster and more efficiently than before.

Data gets personal

Learner data will enable better personalisation of learning to individuals. Personalisation, relevance of learning content and smooth delivery of personalised content to all platforms from PCs to mobile phones is key to the success of long-term learning initiatives. Big data not only informs HR about how well individual students performed on a test or how quickly they finished an e-learning module, it also offers insight into every student’s individual learning path and allows learning providers to respond to individuals as they encounter issues.

A personalised, individual approach is key to successful learning delivery – even the most effective use of big data combined with powerful analytics is best supplemented by the human touch. A recent survey* found that 83% of corporate learners appreciate coaching and feedback provided by a personal trainer, while 84% of corporate learners consider a professional kick-off session with introduction to the course to be useful, highlighting the importance of the human factor and ongoing support. One to one coaching and active use of big data offers the best combination to deliver a personal learning experience that is just as effective as costly one-to-one training while being available 24/7.

Multinational companies are increasingly looking to ensure consistent delivery of training programmes to staff across all locations. More often than not, they are focused on delivering consistent communication skills training, getting all employees up to speed with foreign language skills to allow them to communicate effectively with each other, as well as with partners and customers.  Research has also shown that 89% of corporate learners appreciate the flexibility offered by online language training and 80% of corporate learners report an overall positive outcome from their online language training*. With big data and the right analytical tools, L&D professionals are able to track an entire learner population at multiple locations throughout the learning process. 

Data helps organisations to understand where current skills gaps reside – or might be in the future. It can unlock enormous potential for an organisation’s talent succession strategy and workforce mobility. For example, a skilled employee with a solid grasp of English working for a subsidiary in France may be transferred to fill a temporary or long-term skill gap in a UK subsidiary.

Big data underpins standardisation

Big data also helps to identify patterns that will support the standardisation of learning modules across borders and for the entire organisation. Standardisation of terminology is crucial for large multinational manufacturers looking to guarantee an effective production chain. For example, one of Speexx’s customers, a major car manufacturer, has 42 different terms for a single small part of a car engine. These terms are unique to this corporation and needed to be consolidated so that they had the same meaning for more than 50,000 staff across five continents. Big data analytics has enabled the car manufacturer to build and measure the usage of a standardised glossary across the entire organisation.

Increasing use of personal data tends to go hand in hand with raised concerns about the privacy and security of that data. Data privacy regulations vary from country to country and the level of concern about privacy issues varies accordingly. However, these concerns can and have been overcome as learning solution suppliers have become expert in navigating global privacy regulations.

Perhaps the greatest challenge facing HR and L&D managers has been the requirement to collect as many types of learner data as possible and feed them meaningfully into a central talent or learning management system. There is a pressing need for learning content providers to develop custom APIs that will interface with learning systems in a way that goes beyond the simple view of learner data that standard interfaces allow for.

Widely used technical standards for e-learning system interoperability, such as SCORM (Sharable Content Object Reference Model), did not go far enough in the big data world. However SCORM is evolving fast and in its new incarnation as the Tin Can API it offers a new specification for learning technology that makes it possible to collect data from the wide range of learning experiences a person has online and offline, using multiple technologies, in a consistent format.

As the technology matures, HR and L&D professionals can plan to incorporate big data into their global workforce development strategy. Individual learner data has always been key to the most effective learning delivery and the technology is now available to turbo charge the collection and analysis of learner data to achieve the most effective and consistent training delivery.

*Data source:  Global audit of HR and L&D professionals and senior managers carried out by Speexx from sample size is 72,197 Speexx students, during the period 01/06/2013 – 31/05/2014 across Europe, Americas, Asia and Africa.

Author Profile Picture
Jamie Lawrence

Insights Director

Read more from Jamie Lawrence

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