Writing my previous post about digital banks got me thinking about the widespread use of analytics. In his book Digital Bank, Chris Skinner states that data should be seen as the most critical asset for digital banks. Actually, this holds true for almost every company nowadays.
If you don’t have data of good quality, what do your management reports actually mean? Your data quality must be perfect, and you need the right people to perform the right analyses on the data and the right systems to present the results the right way. Let’s look more closely at each of these topics, and delve into some specific articles that discuss the different aspects of treating data as an asset.
Everyone has a stake
Keith Collins, CTO at SAS, adds something very important to this conversation about data ownership. In his post, 4 tips for modern CIO's Collins says data should not be only IT’s concern anymore; it should be spread throughout the entire organization. IT does not control all the data but the CIO needs to think of how he gets all the data, brings it back together and analyzes it to get answers. In banking this could mean getting data from Risk Management, Fraud, and Marketing, to analyze this and get answers about which customers are of great value for the bank, or which customers make the bank lose a lot of money.
Self–service business intelligence and data visualization
With self-service business intelligence, business people can also analyze their departmental data themselves. This is seen more and more in multiple organizations. In order to facilitate this, the data must be of good quality – no ‘multiple versions of the truth’ can exist.
But how do you keep track of the data that business users are accessing in a time where data is growing faster than ever before? Analise Polsky points out that data visualization is the answer to this question. The human brain can’t process more than one value at once. However, if you present data in a visual way, the brain can make sense of a lot of data in one glance. With data visualization and self-service BI, business users in banking can analyse the data for their department and discover new trends, which they can use in marketing campaigns, for example.
Careful steering
Good data quality is then still the issue to solve. The first step for data quality is good data governance: a formal layout of your organization in terms of data ownership and processes. Tamara Dull, thought leader on data governance and big data, describes in her post about how to do data governance right. This is especially important for large organizations like retail banks.
Texting your way to greater value
Data nowadays not only comes in ones and zeroes. Most organizations need to analyze text as well. Think about hospitals that want to analyze diagnoses and anamneses, or a bank that wants to know what is said about them on social media. As Annelies Tjetjep points out, we need a way to analyze text in an objective way. Banks can then measure the sentiment about their products and brand, and find creative ways to improve.
Banks are no different
In short, there is a lot more to "data as your most critical asset" than you might think. It is all about how you incorporate more (good quality) data into your systems, spread the use of predictive analytics throughout your organization and ensure the quality of reporting in every department. Another interesting article about using data across the organization comes from Adrian Jones. Banks are no different in this respect. In fact, in order to be relevant for your customers, the most basic thing to do is to have your data in perfect shape. Only then can you keep up in this digital world, which will soon be dominated by digital natives.
