Big Data is no magic, Innovation Management is

Image 1 of 1

In this post, Oksana Denysenko talks about how Big Data can influence the work of the Innovation Manager of the future. Leading up to the Degree Show she shares her perspective of the Phoenix as Innovation Manager.

People have been talking about Big Data for a number of years now, and especially in the last year or two it has become very hyped-up. There have been a number of early successes in this space, notably in the retail sector where it allowed to identify consumers undergoing a life-changing event (university degree, marriage, child-birth) and to target them accordingly. However, people have expected a bit more than that: they expected Big Data to drive transformative innovation, and so far it has been driving incremental innovation, at best.

One might argue that Big Data is still in its infancy, and there is some truth to it: many players are hamstrung by legacy IT systems which make it difficult or impossible to collect the data; the linkages between different data pools are difficult to establish; the data is not clean, and the analysis software is cumbersome and expensive to use; etc. One might also argue that those issues will be overcome soon, and looking at the progress made so far this seems a fair bet.

This however does not address the fundamental problem of Big Data that starts shining through, now that the technology is getting up to par: in order to innovate with Big Data you not only need data scientists, you need innovators, and those people tend not to be the same. The data scientist is one cog in the machine, but he or she is not the magic unicorn that suddenly will lift the organization to a new level. On the contrary, it is well known that innovation is an organizational capability that only works if its relevant parts work in unison, and data scientist will not generally have the “conductor” skills needed to lead the transformation within an organization.

In my thesis, I have looked at what organisations need to do to innovate their business based on Big Data. For that, I have worked with a start-up in this space, looked at number of businesses that are already employing Big Data techniques – with varying success – and have analysed all of that within the context of the current academic discourse in the Innovation Management and Business Strategy spaces.

My main conclusion is that Big Data is indeed an exciting opportunity, but that it needs to be lead and driven by someone who understands the strategic innovation framework in which it is to be developed and employed. I also concluded that – when used for transformative rather than an incremental innovation – Big Data goes well with the “Blue Ocean” framework where companies are trying to expand into adjacent, less competitive areas of business instead of fighting to death in their own little “red ocean” segment.

In many situations, Big-Data-driven innovation would call for an innovation manager of the “Phoenix” type who is not afraid of tearing down the status quo (and legacy systems) so that a new business model can arise from the ashes.‏

To learn more about the Phoenix and Oksana’s research, stay tuned for the upcoming MAIM 2015 Degree Show, taking place at Central Saint Martins in the week starting on the 24th of June.