Putting the ‘I’ Back into IT: Future Data Strategies, Big and Small
Situational awareness – the Big Data/Enterprise IT schism
“In the future, we might not even need large banks.” This comment wasn’t made by an idealistic start-up founder, but by an IT executive at a major bank, asked to consider the future of finance. He was referring to developments such as peer-to-peer payment services, crowd-financing models for entrepreneurship, and the Bitcoin crypto-currency, all of which are enabled by novel patterns of data use. Such revolutionary sentiments are in the air today in many sectors. As shown above, there are clear signs that a broad data renaissance is under way.
Figure 1 – There are many signs of a data renaissance
In his recent best-seller The Signal and the Noise1, Nate Silver argues that radical increases in information availability tend to lead to organizational revolutions. For example, the content of Martin Luther’s Ninety-Five Theses was not particularly remarkable for its time; the reason it catalyzed the Protestant Reformation was that new technology (the printing press) enabled this information to be distributed broadly.
We see similar signs of both renaissance and reformation today, not just in the explosion of data volumes and types, but in society’s ability to use this data to better predict developments as diverse as customer behaviour, molecular interactions, presidential election results, individual athletic performance, storm weather patterns and flu epidemics.
Renaissance and reformation are also good metaphors for the challenges these opportunities present to Enterprise IT. While processing data efficiently will always be important, companies must also learn to explore and apply data in new ways – more like art studios than manufacturers. This will require deeper and different skills, grounded in mathematics and new data stewardship philosophies.
We started this research with the ambitious goal of exploring ‘the future of data’. Our conclusion is that organizations must prepare for the growing need to put the ‘I’ back into IT. As technology becomes ubiquitous, novel uses of data – Big and Small – will become a key form of both competitive advantage and business model innovation. This report provides a wide range of concepts, examples, frameworks and recommendations to help clients prepare for this increasingly data-driven future.
Figure 2 – The gap between expectations and behaviour
There is clearly tremendous potential in today’s emerging data technologies. Firms can now better understand customer dynamics, forecast business trends, develop new data-driven business models and embed information into our day-to-day lives. We are steadily gaining the ability to quantify the societal and business zeitgeist, often in real time.
However, opinions regarding the urgency of these developments vary widely. During our research, we were struck by the schism within today’s IT community:
- Big Data, open data and ‘data science’ advocates speak in revolutionary (even utopian) terms about the power of new and better information and algorithms to answer previously unanswerable questions and drive new business approaches. Companies such as Google, Amazon, Facebook, Netfl ix, Twitter, LinkedIn, Bitly, Intuit, Zillow and many others have access to powerful new data sets which they will surely turn into important forms of value.
- But many CIOs, well versed in the history and challenges of CRM, data warehouses and other business intelligence systems, tell us that long-standing information management concerns such as integration, architecture, governance, security and the high costs of ERP are still dominant inside their firms. Interest in new data uses is typically of secondary importance.
While an enthusiasm gap between technology evangelists and busy corporate customers is par for the course, today’s disconnect is reminiscent of the early days of personal computers when many Enterprise IT organizations were similarly focused on existing priorities, but soon found themselves on the wrong side of history. Today’s schism is particularly noteworthy because, as we shall show, in many emerging ‘I’-driven applications, sustained customer commitment will often be required.
1. Nate Silver, The Signal and the Noise: The Art and Science of Prediction, Allen Lane 2012