Pricing and Reference Data Industry Insights

This fact raises the bar and expectation of what is really meant by Enterprise Data Management (EDM). The ability of vendors and internal IT to build and run a centralized repository to collect and cleanse data is not in question. However what is in question is how much of the end to end “Supply Chain” of Reference Data Management is really going to be achieved by implementing EDM alone.

Our clients have been asking us how they can achieve end to end integration and management of supply and demand for Reference Data. They have recognized that it is needed to deliver on the promise of centralized Reference Data Management.

Today’s requirements coming from the business community when it comes to EDM systems are not as straightforward as they used to be. Some consumers want the raw vendor’s data, others want raw plus cleansed, others just cleansed, and others don’t want to deal with a central authority and go straight to the data vendor. This will vary according to asset classes and market sectors in the same firm typically. The trend of consumers getting closer to the data and wanting customized services means a new focus on data delivery SLAs, support for multiple formats and differing cardinalities, delivery status control, data access control mechanisms etc. These are the realities of Reference Data supply chain in 2010. More like a FedEx supply chain than a traditional view of Data Management.

This is where the golden copy approach, somewhat unfairly I believe, got a bad name. Clients are telling us that they now see golden copy system as a subset an end to end solution or Reference Data supply chain. What happens then when the business starts to focus of one data vendor for a particular type of data and where golden copy system now cleanses on a single source? In this case the process being automated is now primarily one of a data supply chain and validation not cleansing in the purest sense. And this is a trend that is gaining momentum, a move away from seeing EDM as broad cleansing alone (putting together a “golden” record with fields from multiple vendors) more to a flexible approach where I can decide I will trust a particular vendor’s data for a particular asset class (e.g. Reuters for US Equities Security Master) and handle exceptions in the quality of this feed alone. So in this situation distribution, access control and exception management to the data is as important as sophisticated cleansing heuristics and complex data model that builds a “golden” record. An extension may be trusting one vendor’s data for all data in one asset class except for pricing fields where they want to validate pricing against another vendor’s data with associated human workflow and automated business rules. This is especially true as firms are consolidating on the numbers of Reference Data vendors they are subscribing to. When the markets were booming the number of times a piece of data was sourced from multiple vendors was irrelevant. Not anymore. Efficiency in the supply chain now has to ensure there is no redundant vendor Reference Data being ordered or erroneously reordered.

According to the APICS dictionary (Association of Operations Management) it defines Supply Chain Management as the "design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand, and measuring performance globally."

This sounds like a more realistic description of what people are trying to achieve in Reference Data Management in 2010 than a the pure focus on collection and cleansing of Reference Data that EDM has long been known for.

The Financial Crisis has created a drive for improved operational efficiency, risk management and regulatory compliance. This has raised the bar dramatically on what is meant by Reference Data Management particularly the end to end delivery on that vision, not just cleansing alone.

EDM may in fact be about to turn into Reference Data Supply Chain Management.