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Too often, business executives are uncertain about the quality of their organization's data. It's an important issue today in part due to regulatory issues, as well as problems with the accuracy of data drawn from disparate sources, including spreadsheets.
Errors and inconsistencies lead to mistakes and lost opportunities-failed deliveries, invoicing blunders, problems with global data synchronization-with estimates of the cost of errors due to unreliable and incorrect data in retail business alone as high as $40 billion annually.
Master data management (MDM) is a part of many manufacturers' business and information management strategies. Ventana benchmarking research indicates that managing master data about customers, products, materials, vendors, charts of account, and location is critical for business success. An approach to MDM that combines business and technology components specific to the kinds of master data typically found in a given industry can help companies improve MDM deployments.
Master data includes the business objects, definitions, classifications, and terminology that, in sum, constitute business information; as well as format specifications for transactional data. MDM makes it possible to define and link master data, including those definitions, references, rules, and metadata. It seeks to establish and maintain a high level of data consistency and reliability.
By these means, a company can deploy and manage processes such that each line of business, regardless of its technological expertise, is responsible for its own data and for enforcing standard practices for conducting business and analyzing information.
Why the IT shortfall?
Manufacturers today rely on complex enterprise applications and information systems to support business processes. Typically, each application or system-whether for customer, materials, product, or services management-1) has specific functionality; 2) handles the business context of data and rules in its own fashion; and 3) stores within it the descriptors of the data. In other words, different applications handle data differently. This heterogeneity means information is inconsistent in different parts of the organization, and leads to complications in exchanging and synchronizing...