Michael Shashoua: Finding Value Through Greater Centralization and Aggregation

Centralizing data for management purposes isn’t just becoming acceptable; it’s thriving, as demonstrated lately by plans for a sell side-backed reference data utility, and the announcement of a partnership between a valuations data software provider and a corporate performance management data aggregator.

The latter effort is a collaboration between Certent, a software vendor focused on management of valuations data supporting the issuance of options, and Vena Solutions, which centralizes data generated as part of corporate performance management efforts.

The partnership addresses the data centralization challenges Inside Reference Data hears about regularly. Even though there is a back and forth about whether Microsoft Excel spreadsheets are appropriate to use if one expects to centralize data, Vena’s offering works with Excel, and its makers point to Excel’s “flexibility and unmatched computing power.”

With Vena’s output working with Excel, Certent allows users of its Disclosure Management platform to use that data in Word and PowerPoint, connecting parts of the data reporting process. Certent’s platform lets users collaboratively review, edit, and comment on financial disclosure data using XBRL coding and HTML code.

Service providers are bound to exaggerate the features of their products or the novelty of their ideas. That may or may not be the case with the development of Certent and Vena’s partnership. Aspects of this particular offering, however, seem like the ideal that firms’ data executives frequently wish for—data management that is all done under one standard, in this case XBRL, which will produce consistency, and without scrapping the ubiquitous Excel spreadsheet tool. Whether you are in the market for something to improve your handling of valuations data for options, or not, it could be a problem-solving approach worth considering.

It’s another example of how the idea of centralizing data for different management purposes is gaining acceptance.

New Value Building Block
The stated reason for Securities Product Reference Data (SPReD), the working project name for a reference data utility whose creation is being driven by major sell-side firms, is to cut reference data processing costs.

It’s another example of how the idea of centralizing data for different management purposes is gaining acceptance.

SPReD undoubtedly will provide value for its creators through cost savings and efficiency. It may not necessarily be a means to source security master data, as Aite Group’s David Weiss noted in our coverage. Apparently, SPReD is not meant to disintermediate the major data providers, although potential users who do already have a reference data processing service in place would be replacing such services with SPReD’s offering.

If nothing else, the SPReD foray by JPMorgan, Goldman Sachs and Morgan Stanley into the reference data operations business is recognition of the value of data. Other investment firms are also starting to recognize the value to be gained from better handling of data, and include that perspective in their data governance planning. They are also recognizing, as are data providers, that data that has been checked and balanced using multiple sources carries greater value for investment decisions.

Finally, value can also be driven by how data is managed to support analytics, or prepared to be used for analytics. Aggregating data in one place, as these major global firms are planning to do, is already in practice internally at CIBC, as Allie Harris, senior director of process measurement and analytics at that firm, has said. “Leaving data where it was is not always useful when you need snapshots for what’s trending,” she said.

With its aim to reduce instances of having multiple single copies of data in numerous locations, SPReD’s value will come from aggregation. Once the utility goes live, which is expected to occur in September, then it can be seen whether its founders will indeed get a better basis for analytics operations as a result.