Data is the new battleground for banks. For all the talk about the importance of digitalisation, the partnerships with digital innovators and the moves into ‘digital first’ models, most banks still do not have a coherent enterprise-wide strategy for data. Trying to compete without a data strategy is like going into battle with both eyes closed.
Banks’ new adversary, Big Tech, has already perfected the equivalent of long-range x-ray vision. It has evolved as a machine to capture, orchestrate and squeeze every drop of value out of data. If banks want to succeed in the new data battlefield, they must rapidly develop the same broad but granular understanding of data and how to maximise its value.
The crazy thing is that banks have all the data they need, but it is in different systems, owned by different functions and in different formats. Big Tech thrives on creating data gravity: just like the gravity of a planet, the more massive the data the more data it will draw to it. Bigger data means better, more cost-effective analytics and better insights to drive out cost and deliver better customer experience. This is Big Tech’s DNA – it is fundamental to the way it operates: collect, collate, analyse, repeat.
Banks need to do the same, but instead continue to fragment data, to undertake small-scale digitalisation projects with small data sets. Digitising specific banking processes or using data to understand and influence behaviours in a specific channel is laudable, but it is limited. These are a series of digital skirmishes that may win some battles but ultimately lose the war. To win, banks must rapidly orchestrate all types of data across the whole organisation and make it all available for enterprise-level analysis and decision-making.
An effective bank-wide data strategy is a complex and ever-evolving process that is as much about changing attitudes as it is about hiring data scientists and a chief data officer. A true data strategy involves the complex interaction of vision, planning, culture, skills, governance and technology. It generates insights that drastically reduce costs in operations, remove costs in compliance and drive new products and revenue.
So, how do you start to build a data strategy? There are three crucial elements. You need a defined vision of what you want (and need) to achieve and roadmap of how to get there. Support this with a strong governance model that transforms data from ‘stuff’ that exists piecemeal all over your organisation into a trusted, secure, actionable and reusable asset. The third element is to instil a culture of data and analytics-driven innovation throughout the organisation. Everyone must be comfortable understanding, using and trusting data. Finally, to transform insights into beneficial outcomes the strategy has to be operationalised at scale.
An effective strategy does not sit on the shelf. It is never done. It must be constantly innovated and improved based on new data and new circumstances. If this sounds like a tall order – it is! But the prize is big too. In 2018 McKinsey research suggested the value from untapped data assets could exceed $15 trillion! Over the summer I will explore approaches to creating these crucial elements of a data strategy hopefully providing some useful insights and pointers. But be prepared, the creation and operationalisation of a data strategy is a task for everybody and requires a shift in mindset and culture.
It is clear that the level of change, the strategic importance, and the high stakes of this shift demand the attention of the CEO. It is a process that cannot be left to IT, a CDO, or to individual functional heads, but must be led from the very top of the organisation. Is the CEO ready? Perhaps not, but to prepare themselves for this challenge they need to invest in their own knowledge and understanding of data. So, for the CEO, it’s back to school in my next blog.