Evolving from Product MDM to Multidomain MDM

I’m attending the Gartner MDM Summit in Las Vegas, and this morning I caught a great session by Andrew White on the evolution from master data management (MDM) of product data to “multidomain MDM”.

Andrew started by talking by talking about the strong intersection of product MDM with enterprise resource planning (ERP), workflow, product configuration, and business rules. The market for product MDM is fairly healthy and is actually a little larger than the market for customer MDM.

The initial need to master product data usually arises from having too many copies of product data in different places around the enterprise. Then typically, product data quality issues need to be addressed, but that needs to be addressed as a continuing process, not as a one-time process.

Multi-channel commerce is known as the “sell side” of product MDM, and procurement is known as the “buy side”. There’s involvement with fulfillment and supply chain management, and with ERP and operations. There are many different silos that need to be connected and synchronized (one client I worked with last year had 175 different applications, systems and databases, most of which used or created product data in some way).

At some point, governance has to be addressed. Companies have to go from departmental or business unit governance to enterprise-wide data governance, and expand from single domain (typically customer) to multidomain (customer and product) master data governance.

Andrew mentioned the level of Product MDM adoption – there was software license spending of $432 million in 2008. Certain industries such as discrete and process manufacturing, communications, retailing, and healthcare providers are classified as “hot” according to Gartner (as of Q1, 2010). Retail in particular is almost post-recession. Healthcare providers has more awareness on the buy side.

A common scenario for some is to have a product MDM hub as a system of record, connected to CRM systems for sales & marketing and customer service, to PLM (product lifecycle management) as a system of reference, and to ERP systems (which need the data for their Item Masters). So the CRM, PLM and ERP systems are process owners, but the MDM platform provides the product and material master data, attributes, hierarchies and so on, for consumption by the other systems.

Andrew talked about how the inquiries he gets break down: ERP and MDM: 50%, product data quality: 33%, information exchange: 15%, metadata management: 10% and content management: 20%, and “can I use my CDI hub to master product data?”: 10%.

Andrew talked briefly about the current vendors in the product MDM space: the specialists (handling just product data) such as Hybris Software, Heiler, QAD, Pindar, Tribold, Requisite Technology, EnterWorks.  He categorized Stibo Systems, Riversand and Tribold as being somewhere in the middle between specialists and generalists (handling other domains).

Oracle, IBM and SAP are strong on product MDM and customer MDM. Tibco and Informatica (formerly Siperian) are customer MDM providers that are moving towards handling the product MDM domain. Microsoft is entering the MDM space but their solution (when it is released later this year) is really suited more for analytical use.

And other vendors such as Data Foundations and Orchestra Networks can model any domain of data, including product data.

Through the end of 2013, you might need two MDM platforms. IBM has three MDM products (IBM InfoSphere MDM Server, MDM Server for PIM which handles complex workflow, and their recent acquisition of Initiate). Other strong vendors include SAP, Oracle and Stibo Systems.

The five-year market growth rate is projected at 18%. The Top Five products have 51% of the market. Vendors to watch include Teradata, INformatica, Tibco and Hybris.

Over the next 12 months, product configuration remains an unsolved problem. Companies typically define business rules all over the place. Over the long term, in MDM, that doesn’t work – those business rules themselves need to be governed centrally. The master data and the business rules both need to be governed. Successful product MDM requires business rules governance.

Reference data is another area – price is NOT master data but it behaves like master data in a lot of ways. It needs to be governed and managed. Business process management and its intersection with MDM is another area of development.

Data quality for product data has its foibles. You need to know where you’re starting from. Most importantly, data quality is not a once and done thing, it’s an ongoing process.

The product master data life cycle looks like: Author > Store > Publish / Synchronize > Enrich > Consume > Analyze.

The picture for the future – there are three main “provinces” for MDM: the “thing” province, the “party” province and the “place” province. But vendors typically have a history in a single domain.

Andrew gave a couple of great example of companies that went through the evolutionary process of going from a single domain of MDM to multiple domains over time.

Andrew closed with recommendations for people beginning their MDM process: create a vision of what could be achieved with a “single view of product data”, to start small but think big and deliver value early, and to define data and process metrics early and then to revise then as needed as you go along.

I’ve been a big fan of Andrew White for several years now, and I thought he did a great job today (as usual). He brings a great deal of analysis to bear on the questions involved in product MDM, and provides clarity and insight into where the MDM market is headed over the next several years. If you’re attending the Gartner MDM Summit in Las Vegas, or have a chance to catch his sessions at a future event, I think you’d find those sessions very rewarding.