He advises CIOs to ensure that their RFP requires the solution to be capable of modeling complex B2B and B2C hierarchies, along with the definitions of those master data entities within the same MDM platform.

Mistake 5: Relying on fixed service-oriented architecture (SOA) services.

Shankar points out that reliable data is a prerequisite to supporting SOA applications-meaning, applications that automate business processes by coordinating enterprise SOA services. "Since MDM is the foundation technology that provides reliable data, any changes made to the MDM environment will ultimately result in changes to the dependent SOA services, and consequently to the SOA applications," he notes.

Therefore, CIOs need to ensure that the MDM platform can automatically generate changes to the SOA services whenever its data model is updated with new attributes, entities or sources. "It needs to be truly configurable," he says. In turn, this key piece of an RFP will protect higher-level SOA applications from any changes made to the underlying MDM system. In contrast, Shankar points out that MDM solutions with fixed SOA services that are built on a fixed data model require custom coding to accommodate underlying changes to the data model. (And we all know what custom coding means: $$$$.)

Mistake 6: Cleaning data outside the MDM platform.

Data cleansing includes name corrections, address standardizations and data transformations, Shankar says. And while a lot of RFPs ask about data cleaning and data quality, those RFPs fail to ask about how and where the data will get cleansed—outside the MDM system or inside the system. This is an important distinction.

Typically the number of source applications that provide reference data to department-level customer data integration (CDI) or product information management (PIM) solutions is typically small. In these cases, Shankar notes, the data can be efficiently cleansed at the source using commonly available data quality tools. However, the number of sources for an enterprise MDM rollout spans multiple departments and comprises tens or even hundreds of systems. "In this scenario, cleansing the data at the source systems is not viable," he points out. "Rather, data cleansing needs to be centralized within the MDM system."

If your company has already standardized on a cleansing tool, then it is important to ensure the MDM solution has out-of-the-box integration with the cleansing tool, Shankar advises. In addition, CIOs who don't know the complete "lineage" of their data will face loads of headaches when it comes time for audit and compliance checks, he notes.