Chief Executive Officers of banks know all about change. Leading responses to new challenges, new opportunities, new regulation and new markets is all in a day’s work. But the existential challenge posed by Big Tech requires a totally new set of skills. It is an entirely different beast that inhabits a totally new environment and speaks its own language. CEOs now need to learn the language of data to survive in the emerging digital world.
Learning a new language later in life is hard. CEOs need to fully commit to accomplish it. Becoming data literate means mastering the basics of vocabulary and grammar. Gartner defines data literacy as “the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the use case, application and resulting value.” Extending the language analogy: the building blocks are an understanding of logical data models – the basic vocabulary; meta data providing rules and information about data is the grammar. Learning needs to go beyond parroting a few key phrases and acronyms. To really communicate in this new language CEOs must not only be data literate – but data cognitive. Language shapes thinking, and to succeed, today’s CEOs need to think data like digital natives.
As anyone who has learned a language will recognise – practise makes perfect. This means rolling up your sleeves and getting into the data ‘lab’. Run some queries, experiment with data to test theories and learn how data can, and should, inform all aspects of business management. It is daunting, and different functions are fiercely protective of their data. But that’s one of the big cultural shifts the CEO needs to lead. Data is more valuable when it is used across the business. Developing safe and secure ways to combine, refine and analyse data at an enterprise level is fundamental to competing with Big Tech. The
Chief Data Officer can help. Spend time with them and use them as a teaching-resource to get more familiar with what can and cannot be done with your data.
As you practise you will build confidence and move from school-level conversations to business-class data fluency. Spending more time looking at and working with data and you will begin to recognise ‘quality’ data, identify attributes and flag anomalies. This will build confidence and essential trust in data. Last year
KPMG found just 35% of CEOs trusted the data in their organisations. This shocking stat undoubtedly stems from a data skills deficit among CEOs themselves. If they don’t know what to ask for, and can’t recognise what they get, they won’t trust it. To stretch our linguistic analogy, if you are not confident in the language then you’ll be anxious ordering food in a restaurant!
Ultimately, no one expects the CEO to personally implement data-analytics programmes across the business. But unless they have the confidence and the skills to accurately communicate what’s needed, to sit at the head of the table and ask the right questions about the menu, then the organisation is unlikely to put the right emphasis on the data strategy.
In
How Google Works, former Google Chairman Eric Schmidt outlines how every meeting revolved around data – it is simply how Big Tech works. Banks need to adopt the same approach. Exploiting data in all scenarios must become second-nature. By modelling the use of data across the business – dissolving silos rather than sticking to narrow data sets that reinforce them, the CEO can define a powerful data culture. Operationalizing data strategy will, just like using language skills, stop data literacy from becoming rusty.
Entering any new market requires investment in understanding the language, culture and business environment. In the Big Tech world, data is the lingua franca informing every decision. Bank CEOs need to learn from them and invest in building their knowledge to become data fluent. There are no short cuts. Throwing money, bodies and tech at the problem will not get you there, as we’ll explore in the next blog.
