How do you pass the EDM usability test?

by Mario Orphanou, Product Manager, Odyssey

While the enterprise data management (EDM) market is in a maturing state, it is still relatively new. Most financial institutions now agree that EDM helps improve straight through processing (STP), however, questions have arisen over its business enablement. A large part of that debate centres on the distribution of data from EDM systems. How many front office, mission critical applications are actually benefiting from the normalised, cleansed data these systems push out? In reality, not many. So why are EDM solutions struggling to integrate data at the front end?

EDM is defined as the process of enabling disparate data sources to share information from a centralised platform. As the name suggests, it intends to manage data content on a business/data-silo (vertical) to an enterprise-wide (horizontal) basis.

Many technology providers have come to market developing the infrastructure to handle the necessary data normalisation and aggregation. While some impressive data modelling has entered the fray, vendors have often struggled with getting data to the end systems that need it. They have in effect done little more than solve a data warehousing problem. From a product management perspective, the industry forgot about the users. This can be attributed, in part, to a back office product development focus. EDM systems were (and still are) intended to handle the critical operational data associated with instruments, products, customers or counterparties. Their function remains largely administrative, consolidating all the internal and external data sources vital to the execution, analysis and settlement of a trade. There is no question that EDM is a critical piece of back office infrastructure.

However, some EDM systems have come unstuck with regard to their integration to front-end systems. In particular, earlier solutions addressed integration as an afterthought and are consequently dealing with a spaghetti farm of legacy infrastructure as well as huge variance on the nomenclature of data terms from both internal and external data users and/or providers.

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