Why Data Management Will Top C-level Agendas in 2016

While some progress has been made to consolidate back-office technology, there is still work to be done–a key area of focus this year will be data. In 2016, we believe that outdated and manual data management processes in the back office will increasingly be viewed as a liability and cost to the firm. Executives are taking note and will look to restructure their approach to enterprise data management.

We expect the industry to go through a fundamental shift, and to focus on developing a more efficient approach to data management.

There will be a complete re-evaluation of current industry best practices, associated costs and returns and a renewed commitment to implementing improved data management that will deliver substantial value to the firm. This reform will extend beyond short term priorities such as how to meet the next regulatory or investor demand, and instead focus on how to create a sustainable data management model that ensures data flexibility, accessibility and reusability for the long term.

Our industry is currently going through a transformation sparked by regulatory concerns regarding systemic and liquidity risk, and that focus has left firms responsible for far more data than ever before.

Asset managers are now at a tipping point in their ability to efficiently manage the volume of data for which they are responsible, which is why data consolidation projects that lower costs and remove the risks associated with data fragmentation will become more important.

Streamlining and optimizing their data management processes as a way to reduce risk, manage cost and create new business opportunities is of paramount importance for this year. We already see more discussion about what an industrial strength data management model will look like, and the debate on data warehouse versus data lake is gaining momentum.

As Domenic Ionadi wrote in a previous blog post, the structure of data warehouses seems to be too rigid to respond to rapidly changing requirements on firm data, but promoters of the data lake model have yet to prove that it will provide sufficient structure to be sustainable on the long run.

Our view is that the right model is somewhere in between.

Asset managers will need more flexibility, accessibility and reusability from their data than a warehouse has traditionally been able to provide. That said, data models will also need rules-based logic baked into them, which requires more structure than the typical data lake is going to be able to provide.

Data availability and reusability will be essential going forward because it will help firms to future proof their systems against new demands from regulators and clients alike.

The best data management models that will eventually arise will be the ones that will enable firms to collect, normalize and access all of their data, at any time, for any purpose.

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