I am currently on the topic of analysing trends and knowing customers’ needs even before they know it themselves – as a starting point for innovation. In the previous delivery I looked at two specific “tools” for accomplishing this, namely trend spotting and scenario planning.
We live in the information age / digital revolution / computer era, name it what you want, but what all these terms have in common is that information (in digital format) is available on virtually everything and in gigantic quantities, and this fact has some serious implications for innovation.
Big Data is big. I want to stick my neck out and make the statement that “Big Data” has become an even bigger buzzword than “Innovation”. It is insightful, startling and sometimes even downright scary in terms of what is being unveiled of big data and its predicted impact on industry, society and life as we know it.
As usual I want to start with a definition. As with innovation there are many definitions for the “phenomenon” of Big Data, but in my view the one that explains it best is the one from the Oxford Online Dictionary: “Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions”.
And some history, according to Forbes, the first documented use of the term “Big Data” appeared in a 1997 paper by scientists at NASA, describing the problem they had with visualization (i.e. computer graphics) which “provides an interesting challenge for computer systems: data sets are generally quite large, taxing the capacities of main memory, local disk, and even remote disk. We call this the problem of big data”.
So, in the “beginning” it was about the size of the data sets, now the term encompasses the analysis of these data sets and the value it can provide – in whichever format to whomever. I don’t want to go into the detail of how big data is collected, stored, analysed, privacy and security issues, etc. but to make my point about the impact of Big Data, I want to share a few astounding facts and predictions from Bernard Marr, author of “Big Data”. Every 2 days we create as much information as we did from the beginning of time until 2003. Over 90% of all the data in the world was created in the past 2 years. The amount of data transferred over mobile networks increased by 81% to 1.5 exabytes (1.5 billion gigabytes) per month between 2012 and 2014. Video accounts for 53% of that total. This year, there will be over 1.2 billion smart phones in the world (which are stuffed full of sensors and data collection features), and the growth is predicted to continue. The boom of the Internet of Things will mean that the amount of devices connected to the Internet will rise from about 13 billion today to 50 billion by 2020.
But what does this all mean for your organisation’s innovation efforts? Once again, not an easy answer, and it depends from which perspective you are viewing it – are you exploiting the opportunities that Big Data in itself offers (collecting, storing, analysing, interpreting data) or are you using it to advance your own business? I cannot go into the details of a complete Big Data strategic plan here, but let me give you my opinion on the relationship between Big Data and innovation from a rational point of view, and then you can decide on your own “Big Data for innovation” strategy. A business exists because of its customers. The better you understand your customer’s requirements and the better you can meet these requirements, the more competitive you can become. Your customers leave “digital footprints” of their requirements every day. Don’t you think it makes sense to start tracking these footprints…?
The world has become excited about Big Data and advanced analytics not just because the data is big but also because the potential for impact is big, especially for innovation. Next time I will look into the concept of Systems Thinking and its relationship with innovation. I conclude with a quote from sociologist William Bruce Cameron: “Not everything that can be counted counts, and not everything that counts can be counted”.