Intelligent Enterprise

We all desire truth, but for C-level executives, one strategy after another has failed to provide the one version of truth they seek. Truth in this case is consistent, real-time information — about customers, products, locations, employees, manufacturing, financials and any other core business element — that spans all systems and divisions.

Getting functional areas to share data and create a consistent resource drove huge investments in customer relationship management (CRM), enterprise resource planning (ERP), data warehousing and similar technologies. Millions of dollars later, enterprises still struggle to integrate departmental and functional data stores to get to a single, comprehensive view. Each enterprise application engenders its own account of information tied to transactions, so enterprises end up with multiple versions of data. And the data takes many forms, structured as in databases and spreadsheets, and semistructured or unstructured, as in Office documents, e-mail, PDF files, blogs and document images.

Enter master data management (MDM), a practice and technology that helps business and IT improve data consistency and accuracy across all systems and divisions while also identifying and managing interrelationships of core data. The technology consolidates and cleanses data from disparate systems. That concept is not new, but in contrast to past efforts, MDM actively synchronizes and distributes consistent "master data" to target systems so information is harmonized continually. Further, MDM manages the full information lifecycle, so you define data as it is created, monitor exceptions as it changes, and deliver reports and alerts on data quality as needed.

MDM may be the right approach at the right time, answering calls for better data quality and real-time information, meeting the demands of SOA (service-oriented architecture) initiatives and abstracting and shielding your data from changes in applications and business processes.

Take the Journey

"Creating a 360-degree view of a customer is a journey rather than a destination," says Jan-Willem Beldman, team lead for analytical applications and data quality at Mentor Graphics, a global supplier of electronic design automation software. "No matter how much pain you go through, that can't be the Holy Grail."

With ERP systems, many instances of CRM and numerous homegrown systems for sales and marketing, Mentor had no single "golden" source of d ata against which all others could be compared. Rather than try to reach the unattainable, Beldman focused more on data accuracy and integration of financial, CRM and marketing data as part of the company's drive toward SOA.

"We needed to foster agility across the enterprise to unite operational systems and drive performance," Beldman says.

Agility would seem a difficult task for a $700 million company with nearly 4,000 employees in 28 engineering sites and 48 sales offices worldwide. Even more encumbering were the multitudes of financial, transaction, marketing, supply chain and order-management systems that had to somehow synchronize to a unified data set.

Like many enterprises, Mentor first tried to foster consistency through a data warehouse initiative.

"We marveled at how difficult it was to make data conform to the dimensions of the data warehouse and decided it might be better to do integration on the front end, where we'd also make better use of the data," Beldman says.

Serve the Master Data

MDM initiatives are meant to find synergies and rationalize overlapping data in disparate systems. They do so by establishing master data rather than focusing on transactional data. Master data is a widely used reference to data describing customers, products, suppliers, locations, materials, assets and other facets that are most important to the enterprise. MDM lets you define a given data element once, understand derivations of that element in different systems and create business rules so master data can be applied across the enterprise.

Of course, many of these entities are moving and changing targets, but, says Sunil Gupta, a director on SAP's NetWeaver MDM team, MDM is "an active attempt to rationalize and synch data as it is updated, with synchronization mechanisms that connect data from different systems across the enterprise. ERP projects required so much time to cleanse, analyze and run transaction data that once you could describe business events, the data was out of date."

MDM's active synchronization approach delivers clean, consistent data on demand, and it decouples the master data set from applications and processes so it is not subject to changes therein. Vasu Rangadass, a senior fellow with i2 Technologies, contends that enterprise data must become a service in and of itself for MDM to work.

"You cannot have SOA without having a data service, and MDM inherently creates a component within an enterprise SOA," he explains.

Decoupling data from applications frees information from departmental silos so it can be shared with other systems. Such silos are a chronic problem for retail banks, insurance companies, health-care providers and high-SKU retailers-they are overloaded with disparate legacy systems, each with its own data store.

Apply the Rules

Extracting information from silos is particularly complicated in organizations where changes to data are often communicated over phone, fax, spreadsheet or even Post-It notes. In such instances, MDM servers are the key to bringing intelligence to the approach.

"The servers are responsible for coordinating and synchronizing data across product data management, product lifecycle management, ERP and CRM, as well as across spreadsheets, e-mail, images, video clips and other unstructured data," says John Kopcke, CTO at Hyperion.