I often tell the IBM Watson story as a way of describing the future of analytics. Watson – with a large quantity of Big Data behind it – beat the two biggest Jeopardy winners of all time. Although that became the story, the bigger story for me was the business application of what I had just witnessed. Watson showed us how analytics will mature from descriptive to prescriptive. Most companies I talk to are still in the descriptive stage – reporting on that which has happened.

But success in the engagement era requires excellence in collaboration and analytics – and not just any analytics, but a prescriptive form of analytics that leverages insight to drive the intended business outcomes. When Watson answered a question, the super-computer generated several possible answers with a percent confidence associated with each. The answer with the highest percent confidence was then provided. In a business context, this represents a movement towards optimizing outcomes by making the best data-driven decisions and taking the next best action.     

As design patterns change, and the world is viewed from the ecosystem in, the systems of engagement envisioned by Geoffrey Moore will evolve. These systems leverage the four key innovations of our day: Social, Mobile, Cloud, and Big Data. When I ask an audience to pick the innovation likely to have the biggest long term impact, the answer is almost unanimously Big Data. I would argue that a strong engagement enabler is found at the intersection of mobile and social, which may ultimately have a bigger impact – but engagement without context is uninformed. While all the Big Data hype makes it hard to focus on its true role, a major role is to provide the context that informs stakeholder interaction across the ecosystem. Beyond informing interactions, Big Data will better inform operations and drive intelligent processes by effectively and efficiently leveraging a broader base of insight. Ultimately, Big Data will optimize business outcomes by enabling more analytic precision, effectively taking us to the prescriptive stage. 

Big Data is simply the evolution of Information Management (some have called it extreme information management). It will play a role in data management, as Big Data technologies expand and accelerate the data acquisition process. It will enable the inclusion of a broader base of data (both structured and unstructured), delivering more insight to decision processes and more intelligence to drive automation. As Big Data evolves to support advanced analytics, analytic precision expands and Insight consumption moves closer to a Google-like experience – the question and answer paradigm displayed by Watson moves to the business environment. These are all attainable as Big Data, traditional business intelligence, and advanced analytics converge. Analytic applications will therefore leverage this convergence for data management, advanced analytics and insight consumption.

Social, Mobile, Cloud and Big Data all play a role in this emerging era of engagement. In its simplest form, Big Data’s role is to better inform operations, drive more intelligence into our automated processes, inform interactions through context awareness, and optimize our outcomes. Watson showed us the art of the possible and Big Data technologies are emerging and maturing rapidly. But much has to happen before this vision can be realized. The enterprise has to move from the descriptive stage supported by traditional business intelligence, through the predictive stage enabled by advanced analytics to the prescriptive end state demonstrated by Watson. There is a danger in treating Big Data as a separate and distinct entity, as opposed to a step towards the end state. Big data should be viewed as an integral part of the broader transformation journey – the era of engagement depends on it.