The Costs of Mismanaging Reference Data

Loraine Lawson
Slide Show

10 Critical Myths and Realities of Master Data Management

Prevalent myths surrounding MDM alongside an explanation of the realities.

Here's an area where you might not think about the impact of silos: reference data.

Reference data is information that comes from outside your applications; usually, it's purchased from an external source. Good examples of reference data are real-time stock market transaction data or even a product master list or customer address list.

The point is that you're often paying for it. And in some organizations, because of data silos, some of you are paying for it twice or more, according to Fred Cohen, the group vice president and global head of the capital markets and investment banking practice at iGATE Patni.

iGATE Patni recently conducted a survey on reference data, and found a majority of financial institutions are planning to overhaul how they manage reference data during the next two years. One telling finding: Seventy-five percent of the financial services firms surveyed reported they have multiple data silos.

TechTarget interviewed Cohen coming off the survey results, and from what he says, companies can't move too soon on this problem. He said some organizations spend more than $200 million on reference data, then waste about 25 percent of it.

Not only are multiple departments purchasing the same information, but once it's acquired, companies fail to govern it - they don't track where it came from, where it's used or how it's changed.

As you might suspect, financial services firms are having to rethink a lot of data management issues these days. Not surprisingly, they're more concerned with compliance issues than costs, so the article discusses the regulatory pressures around reference data.

I look for this to be a huge issue going forward, particularly as more organizations use data services from the cloud as a way of enriching and verifying their own on-premise data.

There's no reason to repeat the mistakes of other organizations, though, so take a lesson from your friends in finance: Govern your reference data at least as well as you govern on-premise data. And for Pete's sake, unless it's double coupon day, make sure your departments are sharing data rather than paying twice for the same reference data.

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Add Comment      Leave a comment on this blog post
Feb 22, 2012 3:53 PM Prof.S.Subramanian Prof.S.Subramanian  says:

Brilliant thought provoking blog piece..

As Ex-Senior Central Banking Executive, I foresee the need for financial institutions to realize the importance of Data Governance, Data storage optimization, Data cleansing, etc in the context of acquiring and crunching for business analytics, varied and widely dispersed data from both internal siloed sources as also from valid external sources. As against the emerging scenerio to adopt and comply with the requirements of Basel I, II and III, IFRS, COSO, ISO 31000 2009, Frank-Dodd Act, HIPPA, and several other business standards, the costs are bound to be enormous in the management of Data and Data sourcing. The above article must be an eye opener for multi-data driven huge financial organizations both from the angles of efficiency-CRM-, costs savings-bottomline improvements-, as also management of wide-spread business risks and compliance.


Chairman, ACMFI & Chairman, Kensho Information Technology Solutions Ltd.


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