How to drive corporate training with big learner data

Citation

Hopp, A. (2015), "How to drive corporate training with big learner data", Strategic HR Review, Vol. 14 No. 3, pp. 113-114. https://doi.org/10.1108/SHR-03-2015-0022

According to Bersin by Deloitte, 2015 is going to be a big year in the world of corporate talent[1]. It predicts that we are entering a talent world where people data are central to every decision, adding, “Organisations that are investing in analytics teams, analytics tools, and analytics expertise are going to far outperform their peers.”

Big data have already transformed retail and consumer facing businesses and is now set to revolutionise corporate learning, too. Human resources (HR) and learning & development (L&D) professionals will increasingly become “data-enabled”, with learner data informing decisions about skills development alongside demand from line managers.

Making the most of big data is not just about identifying what type of learning and development is needed and which topics need to be covered. It is also about getting better information about how learning is embraced and used, what works and what does not, who is learning and who is not, and why. With the help of technology and analytics, it is now possible to adapt and improve training and learning delivery, as it is happening, based on real-time data about learners.

Learner data can provide unparalleled insight into the learning process. HR managers who tap into learner data successfully will be able to offer the type of responsive and relevant learning that is most effective.

Using learner data to boost global workforce development

• Use learner data to standardise delivery: Analysis of learner data can reveal patterns that will inform the standardisation of learning modules and the standardisation of terminology, as employees worldwide get up to speed with the language and communications skills they need to communicate effectively with each other, as well as with suppliers and customers. It is vital that multinationals bring a shared glossary to global production, and data from language and communications learning can help build a shared lexicon.

• Blend data-enabled e-learning with face-to-face support for best results: In a large-scale survey of e-learners[2], 84 per cent of corporate learners said they found a face-to-face introduction to the course useful, and 83 per cent said they appreciated feedback provided by a trainer in person. A combination of classroom and online training has proven to deliver the best results.

• Offer training through multiple devices to engage learners: The latest technical standards for the e-learning system interoperability allow for the input of learner data from multiple sources, making it possible to collect data from a wide range of learning experiences. Technical standards for the e-learning system interoperability such as sharable content object reference model (SCORM) are evolving all the time. SCORM’s latest incarnation – Tin Can application programming interface (API) – offers consistent collection of learner data from multiple devices.

• Use learner data to personalise the learning experience: Traditional learner data such as test results may be combined with much more detailed data about how a student progressed through the learning modules, flagging up issues and allowing for real-time intervention when learners get stuck. Big data can also help to understand what types of learning modules work best for a particular learner and which do not.

• Tackle data protection: Privacy and security issues need to be taken into account when developing workforce learning based on personal data. Data protection regulations vary around the world and concerns about privacy also differ from country to country. However, privacy concerns need no longer be a barrier to getting the benefits of learner data. As data protection regulations have become embedded, learning solution suppliers have gained experience in helping clients navigate privacy laws.

Once learner data are collected and consolidated in one place, the latest analytics can convert big data into clear, viewable and actionable information. Perhaps one learner responds very much better to video-based learning or field sales people are interacting most with gamified, mobile phone-based training. Another learner may be progressing through the learning very much faster than their peers and might benefit from extra training or promotion.

Talent management as we have known it over the past 10 years is about to be reinvented, with a focus on engagement, experience and empowerment. Personalised learning plays a major role in creating a flexible workplace. Offering relevant skills development to the best brains of 2015 is key to keeping them engaged and productive.

Notes

1. “Predictions for (2015), Redesigning the Organization for A Rapidly Changing World, January 2015”, www.bersin.com/blog/post/Predictions-for-2015–Redesigning-the-Organization-for-A-Rapidly-Changing-World.aspx

2. Audit carried out by Speexx of 72,197 Speexx students, during the period 01/06/2013 – 31/05/2014 across Europe, Americas, Asia and Africa.