Data governance is a trend that has moved back to the forefront of the "how to manage information" discussion. A recent Wall Street & Technology article highlights the use of deeper analytics for trading and points to data management as a central problem for capital markets firms.
While deeper analytics is required to propel the business, one glaring issue that is typically found when analytical platforms are deployed is the lack of completeness, timeliness, accuracy and overall data quality found at many top tier capital markets firms. Yes, believe it or not, this is still the case! It seems shocking after so many years of hard work and dollars spent. Many firms still struggle to understand the impact to liquidity and the G/L or balance sheet when doing various trade-related functions (e.g. pre-trade scenario analysis) for example.
Certainly, the notion of more of adding even data to improve analytics is compelling and there is tremendous value in mining big and small data. However, to make 2013 the year when firms improve their information strategies, formalized efforts should be made to improve data that capital markets firms already work with. The improvement comes from data quality enhancement that is defined and refined by a formalized data governance initiative.
[For more on how capital markets firms are changing the way they manage data to respond to business pressures and regulatory demands, download Wall Street & Technology's latest digital issue: Risk & The Data Management Makeover.]
Establishing a data governance charter, program and action group is essential to create organization, definition and agreement between the business and IT, while avoiding mishaps that typically arise from past data quality projects. This step is critical to operationalize data successfully for analytics, and it must be done in a timely manner. Successes are required to reach the deeper analytics needed for understanding where trade and operational profit, cost and customer opportunities exist.
Impetus to formalize data governance programs are no longer just to meet regulations. IT is pressured from the business side to produce outcomes from these multiyear data transformation 'projects' as well - they are tired of waiting for results. If providing reliable and actionable data to the business aren't enough to persuade the firm to truly work through data governance then perhaps market survival is. Some leading sell-side firms have decided to go all in and attempt to tie existing data efforts into a governance program so they can gain the competitive advantages clean data brings.
We've recently seen the U.S. congress take a large and fundamentally vital component of the future success of the country's economic well-being and merely apply a short-term band aid solution. In many ways, data is as important to capital markets firms as tax implications are to the country -- let's not allow firms to head over the data cliff.