Whenever an organization fails to implement any program, the obvious place to look first is leadership. Data analytics is no different. In a recent study of three-dozen companies who have put in place major analytics programs, EY found that a mere third met the objectives of their analytics initiatives over the long term. Their findings are reinforced by a Genpact survey of managers working at 100 large global enterprises, to which just 26% answered that their analytics program had met or exceeded their expected business outcomes.

Data analytics is no longer just a buzzword and there is little excuse for so many companies to be performing so poorly. The ultimate conclusion of EY’s report was that the reason so many companies failed was confusion in the C-suite around whose responsibility the analytics program was, and the upset to the equilibrium created as the power structure is reconfigured as a result of the introduction of analytics. There are two ways you can see this - as a failure of leadership or a failure of the entire traditional corporate leadership structure. Is it simply no longer fit for purpose? Can companies set up along the lines of old corporate structures enact digital transformation and truly implement data initiatives, or are they destined to lose out to digital startups?

The problem seems to be a simple one if we accept EY’s logic, a lack of clarity around ownership of the data. As there is no natural owner of analytics within the traditional organizational structure, when large-scale initiatives began to be implemented in earnest, the CFO, CDO, CIO, and CTO could all be said to have a claim for the controlling interest.

The obvious starting point would be IT, but this would be to misinterpret what exactly data analytics is. While a data initiative requires input from CIOs and their staff to manage the databases and networks that underpin it, data analytics is a decision-making tool and as such probably falls more under the purview of the CFO, because of their control over the data and oversight of strategic initiatives. But these kinds of arguments could go round and round. In truth, for an analytics initiative to truly succeed, the entire organization needs to be aligned with the goals, all employees must have all the data they need at their fingertips whenever they need it, and the structure needs to be agile enough for anyone to leverage insights as quickly as possible. Essentially, the whole company structure needs to be set up for digital and the culture be data driven. Tech companies have this, and that is why they have been so successful at using data. Incumbents usually lack these qualities and have largely struggled with data as a result, slowed down by legacy systems and layers of bureaucracy.

The problem is deeply ingrained and difficult to overcome. C-suite executives have substantial experience and big egos, and they have often got to where they are by trusting their gut. It's impossible to realize a data-driven vision with this attitude because without full buy-in, the vision will never become reality. Large corporate players may well be testing and adopting digital technologies, yet many still find it difficult to keep up. KPMG found that only third of businesses are able to apply digital in a strategic manner, and just one in five can label themselves as ‘digital proof’. Organizations need to have a clear ownership structure in place for their analytics initiatives, and clear goals around what they want to achieve from the data, but more than that they need to be digitally driven to be truly successful, and it seems like many are sticking their toes in the water rather than diving in. While incumbents have been able to compete for now, the ability to do so will not continue as startups born in digital grow and further develop within their industries. Those without analytics programs will lose out to competitors that do, but those who have not got the set-up to succeed in their analytics programs will eventually lose out anyway.