Tag Archives: PIM
I’m at Barcelona this week for the European Gartner MDM Summit. I had a chance to catch up with one of the Gartner MDM analysts before the event, and we had a discussion about the growth of MDM. He mentioned that MDM will become pervasive within the enterprise as organizations expand its use as a necessary foundation for governing all of their business-critical master data such as customers, products, and so on.
To solve their business problems accurately, companies seek targeted MDM solutions. For e.g., retail, distribution, and manufacturing companies use PIM for merchandising, distributing products, and supplier on-boarding, while financial services, healthcare, and high tech companies use customer MDM with their CRM, such as salesforce.com, for improving customer segmentation, cross-sell , and up-sell. (more…)
With the New Year dawning I wanted to look back at some industry trends from the past twelve months, and then look at ahead at what we’re likely to see in 2010. So, this week: recap. Next week: predictions.
“Multidomain MDM” Goes Mainstream
From its inception MDM was meant to be “multidomain” – a solution for multiple data types. This stood in contrast to CDI or PIM, each of which focuses on a single domain. But with CDI morphing into “MDM for Customer Data” and PIM to “MDM for Product Data,” the terminology got a bit muddled. Hence the somewhat redundant “multidomain MDM” came into common usage in 2009 to differentiate it from single-domain MDM. As we saw with the Gartner numbers that I reviewed in my last post, the obvious benefits of managing all domains via a single platform, easier maintenance, and the advantages of leveraging existing investments, are spurring increased adoption. Still, confusion remained over multidomain MDM in the last year, not just with terminology, but also with capabilities. I addressed this in a late November post, but to reiterate: It’s not just about the data model, a true multidomain MDM hub has to be able to model, cleanse, match and relate.
Proactive Data Governance Takes Root
Many IT decision-makers came to the realization in 2009 that reactive data governance is bad because it is not responsive to real-time business needs. Business users increasingly demanded real-time data availability and data stewards worked to put proactive data governance into place to meet these demands. My friend Dan Power covered this topic earlier this year, showing that authoring data directly in an MDM hub enables firms to decouple data entry from traditional CRM and ERP systems, and establish the hub as both the System of Entry and the System of Record.
Taking Aim At The Reference Data Problem
Early on in 2009 we started seeing a lot of customer activity around the “reference data problem” and that interest remained strong through the year. To quickly summarize: certain business processes, order-to-cash for instance, oftentimes use three or more different systems interacting with each other to complete the loop. If their “look-up code” data isn’t standardized (one uses “USA” the second “U.S.” the third “United States”) problems ensue. As a category, reference data is similar to, though distinct from, master data. Yet the similarities are such that effective MDM solutions are perfect for solving the reference data problem. My colleague Manish Sood blogged on this topic in detail here and here.
Be sure to come back next week to see our bold predictions for 2010!
The current hot topic in the MDM space is multidomain master data management. And rightly so, as multidomain MDM has the potential to drive far more value for companies than limited single-domain MDM initiatives (aka CDI, PIM) that focus on a specific class of data such as customer or product.
We’ve heard interesting discussions that multidomain MDM is just about storing the multiple domains within the data model. That is a major misinterpretation. While it’s certainly true that you need to have a data model that’s flexible enough to accommodate multiple data domains (e.g. product, customer, supplier), the data model itself is not the be-all and end-all of multidomain MDM. It’s a requisite starting point, sure, but you need to be able to do so much more. For instance, the ability to match and merge data across various domains is extremely important. Same goes for data cleansing.
Think of it this way: you’re using a dedicated PIM system. It does a great job of matching data fields in ways that are very valuable in addressing problems with product-centric aspects of your business: supply chain, inventory management, etc. Can this system do a good job matching and merging data fields from multiple domains? Can it provide the kind of data cleansing capabilities you’d need if you wanted to incorporate customer data?
A true multidomain MDM hub will provide out-of-the-box capability to:
- model any data domains
- cleanse, correct, standardize, and enrich all types of data
- match the different types of data and merge them into a single source of truth
- relate across the different types data: customer-to-product, vendor-to-material, contact-to-organization, employee-to-location, etc.
To top it all, the data governance application should support the creation, consumption, management, and monitoring of all these types of data.
So to realize the promised value of multidomain MDM, you’ll need a proven multidomain MDM hub and a data governance application that supports all these capabilities.
Critical master data management (MDM) functionality can be easily overlooked when request for proposals (RFP) are narrowly focused on a single business data type—such as customer (Customer Data Integration) or product (Product Information Management) — or on near-term requirements within a single business function. Consequently, IT teams and systems integrators alike run the risk of selecting and investing in technologies that may be difficult to extend to other data types or difficult to scale across the organization. Worse, such solutions will likely require costly custom coding down the road in order to add additional business data entities or to extend the system to other lines of business. These mistakes are easily avoided, but to do so it is important to keep the following ten capabilities in mind as your prepare your RFP. If a prospective vendor can’t answer in the affirmative to all ten questions, keep looking.
Ten Costly RFP Mistakes to Avoid
1. Will we be able to manage multiple business data entities within a single MDM platform?
2. Can the solution support my organization’s unique data governance needs?
3. Will it work with our standard workflow tool?
4. Is the MDM solution capable of supporting complex relationships and hierarchies?
5. Does the system rely on a flexible Service Oriented Architecture (SOA) model that automatically generates changes to the SOA services whenever the data model is updated?
6. Can we cleanse data inside the MDM platform?
7. Does the system allow for probabilistic matching using an assortment of matching techniques, including deterministic, probabilistic, heuristic, phonetic, linguistic, empirical, etc.?
8. Can the system create and maintain a golden record encompassing master data from different sources, which can be reconciled and centrally stored within a master data hub?
9. Is the solution designed to closely track history and lineage in order to support regulatory compliance?
10. Can the solution be implemented for several modes of operation, including analytical and operational?