Gartner Highlights 10 critical myths and realities of Master data management

India Infoline News Service | Mumbai |

Gartner defines MDM as a technology-enabled discipline that ensures the uniformity, accuracy,

The adoption of master data management (MDM) promises many benefits ranging from business agility and improved business performance to increased revenue and lower IT and business costs. However, according to Gartner, Inc., achieving these benefits often entails overcoming formidable technical, organizational and political hurdles.

 

Gartner defines MDM as a technology-enabled discipline that ensures the uniformity, accuracy, stewardship and semantic consistency of an enterprise's official, shared master data assets. Organizations use master data for consistency, simplification, uniformity of process, analysis and communication across the business.

 

“MDM is the latest attempt to solve the old problem of inconsistent versions of important data at the centre of an organization,” said Andrew White, research vice president at Gartner. “As with any new initiative, there is a lot of hype and confusion, and with hype and confusion comes misunderstanding. Executive sponsors of MDM and MDM program managers must avoid several common mistakes that have been known to derail MDM initiatives in the past.”

 

To clarify some of the confusing and conflicting points of view on MDM, Gartner has highlighted the prevalent myths surrounding MDM alongside an explanation of the realities.

 

Myth 1: MDM Is About Implementing a Technology

Reality: MDM is much less about technology and much more about understanding how business processes are supposed to work.

 

Myth 2: MDM Is a Project

Reality: MDM is implemented as a program that forever changes the way the business creates and manages its master data. However, to adopt MDM will require numerous discrete projects.

 

Myth 3: We Don't Need MDM; We Have an Enterprise Data Warehouse (EDW)

Reality: MDM should/will span the organization across all business units and processes (including data stores, operational and analytical).

 

Myth 4: Implementing ERP Means You Don't Need MDM

Reality: Enterprise resource planning (ERP) generally means a packaged business application strategy, most often centered on a single, large vendor. ERP implied, but rarely realized for the user organization, a single process and data model across the organization.

 

Myth 5: MDM Is for Large, Complex Enterprises Only

Reality: The principle of MDM is applied whenever two or more business processes must view or share (master) data. This means that most organizations have a need for the discipline of MDM even if they don't call it that, or if they implement a separate technology called MDM.

 

Myth 6: Metadata Is ‘the’ Key to MDM

Reality: Metadata is critical to MDM (and many efforts outside MDM), but how metadata is applied in the context of MDM differs by domain, industry, use case and implementation style.

 

Myth 7: MDM Is an IT Effort

Reality: MDM must be driven by the business, a business case, and supported/enabled by IT.

 

Myth 8: MDM Is Just Too Big to Do

Reality: MDM can be and is most presently being adopted one domain or province at a time, and one use case at a time.

 

Myth 9: MDM Is Separate to Data Governance and Data Quality

Reality: MDM includes governance (of master data) and data quality (of master data) — MDM cannot be established without them.

 

Myth 10: It Doesn't Matter Which MDM Technology Vendor You Use — They All ‘Do’ MDM

Reality: MDM is complex; rarely do two organizations' MDM programs look alike. Vendor MDM capability has also focused on specialization across data domain, industry, use case, organization and implementation style. Consequently, vendor selection is critical if organizations are to find the right partner.

 

 

 

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