The power of learning analytics to transform your organisation

Learning analytics has been a hot topic for some time now, but what are the components of a successful workplace learning analytics strategy?

In today’s world, the ability to examine large amounts of data to uncover hidden patterns, correlations and other insights is relatively effortless. For those at the forefront, the use of machine learning and a specific subset of AI can analyse more complex data faster. Alternatively, through effective data management principles, many organisations can establish a master flow of its processes to automate. The availability of Apache Hadoop, a free open source software framework that can store large amounts of data and distribute big data fast for any organisation, has provided a platform to do this all with relative ease. But now we are at a point of capturing this data, how are we using it?

With McKinsey’s ‘Analytics comes of Age’ study showing data use has reduced transactional costs for years, the accelerated increase in electronic data has led many organisations to set up wide consumer data lakes, integrated databases and optimised products/services to better meet their users’ expectations. Data sets and sources have now become great unifiers in creating new, cross-sectional competitive dynamics. Regardless of industry or company size, it manages to squeeze into every nook and cranny. It has revolutionised supply chain operations, banking, manufacturing, retail and sales inventory, not to mention generating its own industry sector with venture capital funding of data start-ups reaching over $19bn. There is no doubt that we are in the thick of framing our learning from data – but is this being done ethically or have organisations limited its use to increase their bottom line?

It is widely accepted that learning analytics can influence decision making. Harvard Business Review Analytic Services study as reviewed by SAS shows real-time customer analytics are a strategic priority. Early adopters are already reaping tremendous benefits on the engagement and revenue front – most successfully creating personalised customer experiences at scale. However, it has not thoroughly been explored if information technologies and digital media can systematically distinguish cases of online manipulation. Some researchers suggest that at its core, manipulation is a hidden influence – the covert subversion of another person’s decision-making power. For a number of reasons, data analytics can engage in manipulative practises significantly easier and therefore makes the effects of such practices deeply debilitating.