The amount of data and their importance to business is growing constantly. There follows the need to study, classify, and especially use them in the right away. To this end, advanced analyitics are gaining significant space and role: they are the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, in order to discover deeper insights and make useful predictions for business development.
Whereas traditional tools concentrate on historical data, advanced analytics focus on current and real-time information to predict future events and trends. Predictive analysis is therefore a sub-category of advanced analytics – and a fundamental one: to be able to master this technology means gaining obvious advantages for essentially any organisation, as by predicting behaviours they stand a better chance of influencing them.
Indeed, advanced analytics are a set of techniques (predictive analysis, data/text mining, machine learning, sentiment analysis, neural networks – just to mention some) that allow, for instance, to better understand consumer behaviours and preferences through the analysis of large amounts of data.
It is a relatively new tool, but big companies are already trying to integrate it into their working process. MIT Sloan Management Review, conducted during 2016, reveals a sharp rise in the number of companies reporting that their use of advanced analytics helps them beat the competition. According to several indicators by Sloan Management, from 2013 to 2015 fewer companies were deriving competitive advantage and other important benefits from their investments in analytics (from 67% to 51%). This was partly due to a surplus of data and partly to the difficulty of putting data to use in a competitive way. In 2016, on the contrary, companies begun to implement advanced analytics systems that allowed them to overcome this hurdle (57% of cases) and to use data insights to strategic purposes such as innovation of business models. Today, companies are able to access larger and larger pools of data and use analytics to inform decision making, improve day-to-day operations, and support the kinds of innovation that lead to strategic advantage and growth.
Their efforts are already leading to satisfactory results: the Data & Advanced Analytics: High Stakes, High Rewards report developed by Forbes Insights highlights that two-thirds of companies with well-established advanced analytics strategies reported operating margins and revenues of 15% or more in 2016. More into detail, 66% achieved revenue growth of 15% or more, while 63% reported that operating margins had increased 15% or more in 2016. In addition, 60% of these companies said they also improved their risk profiles. This said, it should not come as a surprise that over the next 2 years, more than half of the global executive respondents are planning to invest at least US$10m in big data and advanced analytics, and that global demand for advanced analytics market is expected to reach approximately USD 60.44 billion in 2021, growing at a CAGR of slightly above 33% between 2016 and 2021.