[Related: "Big Data, Small Governance: Why Federated Data Strategies Will Win"]

The industry is working hard to rid itself of the toxic assets that caused the markets to all but collapse, but it must also work to remove the toxic data structures that supported them. Times have changed since the crisis hit -- an increased regulatory burden, greater demands for transparency, and a more complex operating environment have meant an exponential growth in data volumes. This has put much greater demand on the infrastructure that supports financial institutions at a time when austerity governs most operational budget considerations. To deal with these conditions, data management needs to get more athletic: strong but agile, flexible but resilient. However, it has become sluggish, overweight and bloated.

The problem has been exacerbated as requirements for pricing, risk management and compliance creep closer to real time. These types of processes, once confined to the middle and back office, are being adapted for the front office to provide, for example, real-time scenario analysis and curve construction.

All of this requires rapid data processing and analysis. Instead of piling on more infrastructure, adding new universal feeds, expanding data warehouses, or putting new terminals on every desk, however, financial institutions should be considering a data detox to purge their workflow of excess bulk, unhealthy flab and dangerous toxins.

In fact, this is what modern data management is all about. It requires financial institutions to look carefully at the data they need and how it will be used. Any data management infrastructure has to be appropriate for the size of the firm and its individual operations. The solution that is right for a medium-size hedge fund is very different from the solution needed by a global custodian with thousands of customers and tens of thousands of employees.

In the same way, individual business units, product lines and investment strategies will all require different data sets, and will consume them in different ways and at different times. Where traders want data on actual holdings, analysts use it for modeling ‘what if’ scenarios.

The key is to ensure that everyone can make sense of, and meaningfully use, the increased information required from them and available to them. That requires a central, streamlined system that has the ability to consolidate, cleanse, and distribute data, and the know-how to know where and when it’s supposed to go.

In essence, data management should support the organization, not smother it. With financial institutions under greater pressure than ever before to enhance their risk management, compliance and reporting capabilities, first they must get their data into shape.

But slimming down the structure is not a seasonal fad or a crash diet. If financial services firms want to detox their data to optimize their operations and decision-making, then a sustained -- and sustainable -- approach to managing information is required. If not, data management -- the lifeblood of any financial institution -- risks becoming a cause of almost fatal sclerosis.