Paul Coffey, Xceed’s Principal Data Architect, urges companies to look beyond the big data hype and explains how thinking smart about data can lead to commercial gain and regulatory compliance

Companies are basically made up of three things: People (who are managed), processes (that are over-managed) and data (which is just not managed enough). Albert Einstein once said “we cannot solve our problems with the same thinking we used when we created them,” and this is the underpinning aspect of “doing” data properly. Companies really need to use this intelligence to think differently.

Paul Coffey
Paul Coffey

In other words, in order to implement smart data solutions effectively, companies must first adopt a data mind-set that includes an understanding of their own current “small” data across their organisation, as well as gain an appreciation of both the breadth and depth of their data. Understanding that will help with realising that “big data” is about broadening the breadth of the data that they can use  to be more effective. Understanding that breadth, with the corresponding depth, can lead to smart data thinking.

What companies need to understand is that big data can be used for competitive advantage, streamlining current business processes AND satisfy the ever-increasing risk and compliance drivers.

Given the commercial and regulatory drivers, more emphasis needs to be put on the importance of data. Yet many organisations misunderstand what big data actually is, meaning they identify “big data challenges” that are not down to big data at all.


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For example: duplication of data repositories and applications gives the illusion of lots of data within their landscape, but actually it’s lots of systems that have data moved between them. This is not a big data issue per se, it’s an “understanding your landscape” issue.

Many organisations need to get to grips with their IT System landscape but more importantly it is crucial to understand their EUC (End User Computing) landscape– which, because it is un-governed, is effectively the Wild West of data and analytics.

Imagine this: You’re the McClaurys and the Clantons when the Earps and Doc Holliday come to town. They impose a set of rules and regulations, which you now need to adhere to. The situation reveals pot holes and pitfalls along the way and before you know it, it becomes apparent that the landscape has been largely ungoverned and its true extent isn’t known.

In the FS industry this is equivalent to the regulator i.e. BCBS, demanding more and more knowledge of data lineage on the landscape. This will become a statutory requirement and the scope of FS organisations needing to evidence this will widen in the coming years.

The thing with EUC landscapes is they have large value data sets within them based on unsupported user spreadsheets and databases. In the vast majority of cases this data originates within IT-supported platforms and is then mashed, merged and aggregated via EUC’s. Even though some FS organisations might have EUC policies covering user developed applications, these “add-on” processes are increasingly difficult to track and trace as the amount of data grows. This makes it difficult to govern and even harder to understand the potential impact a lack of control could have on the business. Therefore it’s easy to see how processes become confused.

Having a clear understanding of the EUC landscape, how data is being used and, most importantly, who owns the data is crucial when it comes to understanding organisational data landscapes. IT cannot govern or control EUC applications maintained in business areas, yet still data exists within and moves between IT and business owned systems. This needs to be addressed and corrected, because even though opaque, it is business critical.

In terms of banking, the first steps to this were put in place in January 2013, when the Basel Committee on Banking Supervision (BCBS) published fourteen mandatory principles to strengthen banks’ risk data management, calculation and reporting practices. These principles form the BCBS239 and have been put in place to enhance risk management so firms have a full view of associated risk within their decision-making processes.

Unfortunately ownership is where most companies are stuck – few have managed to apply the appropriate governance. The principles of BCBS239 are crucial in beginning this understanding and bringing data to top level view, so correct data governance can be put in place.

At the end of the day involving your business community is vital in understanding your organisational data landscape, gaining control, and enabling success. Having a full knowledge of the data landscape will not only increase regulator confidence, it will increase the effectiveness of your Enterprise PMO (assuming you have one) and improve change management effectiveness.

Having a solid foundation, robust management and governance are a sure way companies can effectively implement smart data thinking and technology into their operations to see a commercial gain and keep that regulator satisfied…