Over the years we’ve covered the topic of strategic data thinking many times and from multiple angles, for the purpose of this blog we’re calling it data literacy. As business leaders take a break on summer vacations now is a good time to reflect what data literacy entails once more. In our conversations with c-level executives at banks and financial institutions around the world one common theme always crops up. How do we change our operating model to be more agile, responsive and customer experience focused in the digital, mobile first world? There are many responses and many approaches to meeting this challenge, but two elements are fundamental: creating enterprise-wide data foundations and moving these to the cloud. It is in this context that further reflection on what data literacy really means is useful.
CEOs, COOs and CFOs alongside other board members have made progress in learning the language of data at many banks. Now they need to leverage that knowledge to help deliver the flexible, cost efficient and profitable businesses they seek to build. Think of it as moving from the classroom to real world application. The focus shifts from knowing the ‘what’ of data to using that knowledge to set a strategic framework and making the right decisions to fully leverage data in long-term strategic view.
SETTING THE FRAMEWORK
As leaders of the business no one expects you to be the expert linguists of data, conversing fluently as day-to-day challenges are addressed – you have data scientists to do that. But it is vital that senior leadership creates the context in which those data conversations happen. Data literacy for the CEO means having the long-term view and ensuring that the increasing number of data-driven conversations draw from a common lexicon and contribute to a consistent library. Their role is analogous to the Académie Française– policing the language to keep it fully aligned with the strategic vision and preventing side projects from undermining the viability of the whole. That means knowing enough to ask the right questions, having the linguistic confidence to challenge assumptions, and the understanding of which projects are contributing and which detracting from the Bank’s ability to change its operating model.
The shift to the cloud provides a good example of where and how this data literacy is needed. Some banks we speak to are ready to shift all or most of their core systems to the cloud. They want to do this to save money, but also to leverage the flexibility and speed that the cloud delivers. But most banks are either not yet ready to make the move or are taking a more incremental approach. Fast, lower-cost single application projects can be effective in delivering a rapid return from cloud-based data analytics – but will they support the wider strategy? This is where a proficiency with the language of data is critical. CEO’s need ensure that speed and experimentation don’t limit strategic potential in the future.
To deliver the levels of service and quality of experience now expected by customers used to one-click gratification thanks to the explosion of mobile apps in every aspect of their lives, banks need to leverage integrated data. They already have vast troves of high value data, but much of it still sits in isolated silos. Shifting silos to the cloud, or worse, creating new cloud silos with unintegrated point solutions will not address this core need. CEOs need to leverage their data literacy to understand that even though small-scale, specific cloud-based analytics can deliver rapid returns, without integration and scalability they risk recreating fragmentation that will hinder future progress.
DATA LITERACY IN ACTION
That’s not to say that CEO’s must champion vast monolithic frameworks that stifle innovation and agility. A language can evolve and allow room for experimentation and diversity. It’s just a question of maintaining an informed overview that keeps everyone aligned to shared strategic goals. Our work with a large regional banking group in France which owns 17 regional banks among other financial services organisations, demonstrates how the two can go hand in hand. By creating an enterprise-wide data ecosystem Teradata has enhanced data sharing across all business unites. Consistent data models enable easy cross banks analytics supporting both the day-to-day needs of local banks and business units as well as the strategic goals of the Group. Over 30,000 business users across the Group use a single data marketplace to access timely and quality data to drive better decision making across risk, fraud, marketing, regulatory compliance and profitability. This high-level approach to data literacy not only supports today’s requirements, but lays flexible, scalable and fast foundations for new analytic use cases, new business and innovation. This model can shift to the cloud as a whole or incrementally as and when the Group is ready.
BEWARE THE LURE OF THE QUICK FIX
The lure of single application, or single department cloud deployments with the promise of rapid ROI can be hard to resist. But this is where leaders need to put their data literacy into practice. Is it enough to demonstrate fast returns in a small area – or do you want to leverage your data to build best in class solutions that not only solve short-term tactical issues but put your organisation on a par with the best of the best worldwide? To simply compete feature by feature with today’s competition, or to leapfrogging them to build the Bank of the Future? As we’ll explore in the next blog, Gartner ranks Teradata’s technology as best in class – and that gives leaders the ability to think beyond the tactical to build real and lasting competitive advantage. So, as you reflect on data literacy as an asset consider how you want to deploy it – after all its not what you know, but how you use that knowledge that matters.