Regulatory reform, competitive pressures and the need to optimize data across the enterprise are pushing custodians, service providers, consultants and securities firms to constantly refine their reference data management strategies. As their strategies evolve, all players in the operations matrix will have to hone their relationships with their market data vendors, which should be collaborative but often aren’t.
This is a major finding from a panel discussion on the challenges of reference data initiatives that was part of FTF’s Reference Data Seminar, held yesterday in New York.
Yet getting to collaboration is a challenge because it requires market data vendors to provide a “Trifecta” of good service and high quality data at the best possible price, said one panelist. They go hand in hand and market data customers should not assume that they have to pay ever-higher prices for quality and service, according to the panelist. Customers also have to be vigilant in dealing with market data vendors. “Vendors like to duck and hide with services,” the panelist added. In order to protect themselves, customers have to insist upon service level agreements (SLAs) that have “teeth and penalties. … Of course, the vendors don’t want to do that.”
Vendor consolidation in the market data industry is another major challenge as the turnover in vendors’ sales and support staffs means that customers often have to work with inexperienced personnel that are quickly replaced. “I’m very frustrated with one vendor,” said a panelist. “As a result, that vendor is not the first vendor I will call.”
Another panel participant suggested that customers create a data vendor scorecard that measures, compares and contrasts offerings and SLAs. The scorecards can help market data users set expectations and help vendors meet those needs. “The good ones look forward to the scorecard,” said the panelist. “It’s a very powerful tool.”
The panelists also suggested customers consider some other tactics that help in dealing with market data vendors and in improving data management:
- Define a data governance strategy for all reference data initiatives that meets specific needs;
- Establish a meta data layer that avoids a dependence on a single vendor;
- Build a data dictionary to prevent ambiguity;
- Avoid vendor contracts that are restricted to lines of business—aim for enterprise-wide support;
- Consider multiple hierarchies for classifying data such as organizing data by client, process and system levels;
- Articulate what the internal business unit wants from a vendor as well as the drivers for buying data offerings;
- And get the backing of the major internal players and business units especially for establishing data governance rules.
Panelists also stressed that, while contentious, vendor relationships need not always be riddled with strife. Some vendors are actually offering products that offer time series and real-time support, are rules-based, and offer more agility than homegrown systems, said a panelist.Those qualities will prove very useful as customers move away from siloed data and toward the current Nirvana of integrated, enterprise-wide data management. “That is the most significant issue of the day,” a panelist added.
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