Global governance is what makes big data valuable

The bigger big data becomes, the more valuable it gets. Most CIOs understand that the benefits of analytics increase when you collect, store and analyse data from more sources, in greater quantities and without latency. Give a global fashion retailer access to real-time data from its entire store footprint and it can not only react more quickly to new trends but also keep a tighter rein on costs across its supply chain. This is big data working as a strategic asset. 61 per cent of organisations in recent Capgemini research acknowledged that big data is now as valuable as its actual products and services.

But the bigger big data becomes, the harder it is to manage. For CIOs, it’s a problem as intractable as it is inevitable. Sooner or later, you run into the laws of physics. If our fashion retailer wants to store all its transactional data in the cloud, enabling the firm to run complex analytics on customer behaviour patterns, the CIO knows all too well that the minute the data exceeds one or two petabytes (incidentally the point at which it becomes really useful) it also becomes immovable.

This is of course great news for the cloud providers. With widely accepted open standards only emerging at a low pace, the illusion of choice for now is cloud’s dirty secret. Once a customer is signed up, switching between providers becomes physically impractical.  The most cost-effective method of moving a petabyte of data from A to B has long been to rent a room from your cloud provider, transfer the information onto a lorry-load of hard discs, and FedEx them to the data’s new home. The irony for organisations navigating the transition to digital business is that big data, the Holy Grail of transformation, is simply too big to handle digitally.

So how do global businesses run global analytics on immovable data? The solution is to behave like a mining company. The size of the mine dictates that you take the digger to the mine, not vice versa. If the data is too big to move, you take your analytics to the data.

This is fine in principle, but the nature of global business operations is that data tends to be generated according to the local environment. Our fashion retailer, for example, may have its marketing operations and headquarters in the UK, manufacturing ops in India, and a growing sales market in China. With hundreds of millions of Chinese consumers, the business needs access to as much transactional data as it can lay its hands on.