How Data Science and Analytics can help Hyper-personalise Learning at Scale

High outcome personalised learning, deployed at massive scales, has been a long unfilled goal for L&D teams, especially in the behavioural learning space. The complexities of designing and implementing such in-demand high RoI learning journeys has been a deterrent for business leaders for long.

“The latest advancements in Data Sciences and AI will mark a generational shift in how such complex problems are addressed,” said Ranjan Kant , Co-Founder and President of FinTech startup Arthmate.

Formerly a Partner, Data Sciences, with BCG, Ranjan elaborates, “With vast amounts of data available and the tremendous processing power that cloud computing offers, the industry is already migrating from a one-size-fits-all ideology to high levels of personalisation at scale.”

Anand Tuli , Head Analytics and Decision Sciences at Vedantu, dispels the notion that such implementation is difficult to achieve. “It’s not only possible, but also the need of the hour,” said Anand. Sharing some examples from Vedantu, he says, “With the Data Analytics and Sciences application last year, Vedantu reported the highest number of selections into IIT and NEET, as well as an approx. 5X growth in marketing RoAS. I believe with the advent of generative AI and autonomous systems, data sciences will play an even more significant role in personalisation at scale.”

Another learning-tech startup, Vani, has been implementing such a solution in the Communication Fitness space for corporate learners. Explaining how Vani is designed to hyper-personalise a learner’s learning journey, founder

Ashish Kumar Jha says, “To help a learner build Communication Fitness, we record, transcribe and analyse their communication patterns determining precise learning needs. All the gathered intelligence also includes each learner’s own day to day communication scenarios enabling outcome driven learning. We then use algorithms to design personalised roadmaps for any number of learners, treating each learner as a segment of one, ensuring that their learning journey is not only effective but also dynamic.”

With all these innovative ideas already in practice, we are witnessing the rise of next generation learning and development using cutting edge technology. Data science and AI have the potential to revolutionise learning.

The future holds immense opportunities in not only developing hyper-personalised learning programs that are outcome oriented but also doing this at scale to meet the desired business outcomes of large organisations.