In-Depth

Masters of Their Data Domains

The Big Idea

PLANNING TO DEVELOP

  • Enterprise apps increasingly support the services approach to development. ERPs are no exception, featuring data schemas, object sets, APIs, sticky middleware and GUIs, among other tools.
  • Some enterprises are using these industrialstrength ERP systems as development platforms for service-oriented architectures.
  • New ERPs are much easer to work with, say systems integrators, but if you're using them as app dev platforms, you'll need to carry a heavy tool bag.

Picture the old, painfully funny Abbott and Costello “Who’s on first” routine in which the comedians drive each other to distraction by misinterpreting the names of players in a baseball game. When many companies try to view crucial customer or product data, misinterpreting basic information is a common problem. Enterprise apps often provide different versions of what is supposed to be the same data—versions which are incompatible in structure, definition and content. Only the results aren’t funny. They are costly and affect competitiveness.

That’s where the concept of master data management comes in, and not surprisingly, MDM is defined in different ways. IDC describes MDM as a set of processes to create and maintain a single view of products, customers, accounts or locations, through a physical or logical hub across the enterprise or, in some cases, across enterprises. Although the concept is simple, getting there isn’t.

So vendors and consultants have been gearing up with technology—some of it old, some of it borrowed and reworked from other data-handling tasks, and some of it new—to give orgs a chance to get data right once and for all. Vendors vying for this new market range from startups and niche vendors such as Kalido to the venerable Big Blue.

IDC expects the annual MDM market to reach $10.4 billion worldwide by 2009.

Businesses are paying more attention to MDM for several reasons, according to IDC research. Many enterprises must comply with federal mandates. Companies are also looking at MDM to improve supply-chain efficiency.

A single version of truth

"Maintaining a single view of products, customers, locations and financial accounts is a significant challenge," says Henry Morris, group VP and GM for IDC's application strategies research.

"At its heart, master data management involves changing, consolidating and rationalizing core processes such as new product introductions or customer or patient/citizen/supplier registration and ongoing management,” Morris says.

Established terms such as product information management, customer data integration and financial consolidation are attempts to provide a single view of one type of master data, an effort IDC calls applied MDM. Some software of this type came on the market in the 1980s. What's new, Morris says, is the emergence of MDM infrastructure software that is purpose-built to support all types of data, using a combination of techniques from data and content technologies.

Morris reasons there are three types of current MDM scenarios, reflecting the diverse set of projects now being undertaken:

  • Management Reporting Scenario, which reconciles, rationalizes or organizes master data at the hub to drive reporting for compliance and business performance management (BPM).
  • Data Synchronization Scenario, which builds consistency in operations by synchronizing master data from the hub back to local systems.
  • Single Point of Origination Scenario, which requires that all changes to master data originate at the hub for real-time consistency in operations. As the scenarios become more challenging, increasing levels of services are needed.

Alan R. Earls

Master plan to master data
MDM is fundamentally a technology and a business issue. “In order to tackle it effectively, companies must make some definitive decisions about what they want to define as master data—for customers, parts, bills of material and so on,” says Josh Greenbaum, an analyst at EAConsulting.

The business issues are especially complicated because they involve centralization of authority and a level of command and control that most companies are unable to implement—sometimes for good reasons, Greenbaum observes. Many companies prefer a more decentralized business model, but that approach carries a penalty in terms of the additional costs incurred for customer and parts acquisition.

If a Global 1000 company had access to a single master parts list as a result of implementing MDM, leverage in acquisition would be a huge benefit. Still, it’s a balancing act. “You don’t want to start an organizational revolution just to have a single parts list,” Greenbaum says.

Sure, getting 100-percent control over data—master data or any kind of data—is probably impossible. “The real obvious pain points, like customer data, are something everyone can afford to tackle,” Greenbaum says.

People who need people
Andrew White at Gartner believes people, not technology, are the primary challenge. That doesn’t mean the technical challenges are trivial. MDM will have a tremendous impact on the way apps are developed. “Until now, the assumption has been that each app owns its data, but the MDM movement is based on something very different,” he says.

What’s the state of MDM adoption today? Companies have known all along they had a problem; what is new is the recent wave of solutions, which Gartner lumps under a concept called enterprise information management.

So far, White says, it’s the big companies that are putting money and thinking into ways to solve MDM, and these orgs are begging vendors to help. But vendors are only just beginning to realize that in a world of SOA, interoperability is going to be important.

“In order for service-oriented architectures to work, there needs to be a whole layer of master data reconciliation,” White says. Vendors now realize, according to White, if they don’t fix this issue, SOAwon’t happen.

Web master data
Despite the lack of agreement about exactly how MDM will happen, what it is and where it is going, practitioners are helping their customers tackle MDM problems today from a number of different angles. Two companies with comprehensive MDM visions, according to analysts, are Kalido, a spinoff of petroleum giant Shell, and IBM.

Kalido sells two apps: one focused on data warehousing and the other on MDM. The Kalido 8M: MDM product manages and controls multiple types of master data, not just product or customer data. It can take data from any number of systems then support analysis that will, for example, accurately show which items are the most profitable. This type of functionality is a result of the company’s work in BI before it ventured into MDM, says Cliff Longman, Kalido’s CTO.

Kalido’s customers are deploying MDM to manage common business definitions for master data within a workflow-driven, Web-based repository. The repository is then used for corporate performance reporting and analysis to increase its consistency and accuracy, reduce errors and obviate the need for standardization of the underlying operational systems.

Master data can be published and distributed to business people as well as operational systems in order to share the common data definitions more widely. A history of changes made to master data over time is kept to support trend analysis and audit trails for compliance and governance initiatives.

“If you look at our biggest soft spot, it is B2B with complex customers,” Longman says. In B2B environments, customers are frequently changing customers, partners, and products and operate using complex IT infrastructures.

A key design feature for Kalido is using just one table to store all data: “If you change the structure of the data or add new levels and hierarchy to adapt to a change in the business, the programs that access the data will still function,” Longman explains. In effect, he adds, this approach separates the business model from the underlying database schema.

Governance is a big piece
Big Blue is also eyeing the master data problem—and the market opportunity. IBM’s WebSphere DataStage TX enables enterprises to combine data, apps, and messaging system content and deliver the resulting data to any app, business process or end user that needs it. The software, which is built on an SOA, allows the data integration environment to be deployed in an open architecture.

Because it supports e-business standards, WebSphere DataStage TXcan integrate business data (XML and non-XML) regardless of data volumes—for example, a HIPAA claim that has an XML claim attachment embedded inside a non-XML document—while ensuring data quality, according to IBM.

WebSphere DataStage TXprovides “industry packs” to simplify the task of integrating data from disparate sources and transforming it into a format that meets industry- specific standards such as SWIFT, HIPAAand EDI. The software also supports integration of data from widely used enterprise apps from vendors such as SAP, Siebel, Oracle and PeopleSoft.

Technology isn’t the whole battle, says Craig Jett, MDM strategy and marketing executive at IBM: “Abig piece is governance and how you manage your data.”

MDM is accomplished through middleware and services that support data management and put data within the right business context for a particular domain. Data process control through an SOA is a key component of MDM, says Jett. “Ultimately, we lump MDM into data governance, stewardship and change management,” he says.

No need to go global
In a market as potentially large and diverse as MDM, not every vendor is aiming to provide a global solution to everyone’s problem. Managed services provider Liaison Technologies offers Enterprise Content Director, a hosted product information management (PIM) solution, which focuses only on product information. Hosting solutions can cut implementation time to weeks rather than months and provide a rapid ROI, asserts Bob Renner, CEO of Liaison Technologies.

According to Renner, Enterprise Content Director applies adaptive intelligence techniques and data manipulation rules to pull information from data pools, using industry standards such as UCCnet, papiNet, CIDX and XML to ensure accurate data synchronization.

Barbara Mowry, president and CEO of Silver Creek Systems, says her company is focusing on “semantic integration” to deliver MDM’s missing link. What’s needed, she says, is a semantic-based approach that ignores data patterns and identifies real meaning. Once an item is properly understood, it can be standardized, localized and enriched according to the needs of the company and the system.

Silver Creek’s DataLens System, architected as an SOA, employs AI, semantic modeling and expert system techniques to achieve high recognition rates and reusability, and it does it on the fly and with easy scalability, according to Mowry.

Ultimately, any business pursuing MDM is still battling with the oldest IT problem in the world: “Garbage in, garbage out.” But unlike the old days, it’s no longer adequate to merely complain about the problem, you have to fix it.

On ADTmag.com

ILLUSTRATION BY MICHAEL MORGENSTERN

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