Full Description

The identification, definition, preparation, control, archiving, and disposition of data allrequire a sizable investment in labor, supporting systems, and time. The purposebehind enacting consistent, high-quality data management (DM) is to make certain thatthe enterprise reaps a return on this investment. A well-designed DM process ensuresthat customers receive the data they need when they need it, in the form they need, andof requisite quality.

When DM principles are applied using effective practices, the return on the investmentin data is maximized and product life-cycle costs are reduced. This standard is intendedto be used when establishing, performing, or evaluating DM processes in any industry,business enterprise, or governmental enterprise.

This standard describes DM principles and methods using a neutral DM terminology.

The methods of DM have undergone significant changes as paper documentstransitioned to digital data and continue to evolve. As a result, many policies, manuals,and instructions for DM, which mostly addressed DM for defense products, becameobsolete; they described procedures that were adapted to efficient paper-basedmanagement of paper deliverables. This standard is intended to articulate contemporaryDM principles and methods that are broadly applicable to management of electronic andnon-electronic data in both the commercial and government sectors.

Data management, from the perspective of this standard, consists of the disciplinedprocesses and systems that plan for, acquire, and provide stewardship for product andproduct-related business data, consistent with requirements, throughout the product anddata life cycles. Thus, this standard primarily addresses product data and the businessdata intrinsic to collaboration during product acquisition and sustainment. It isrecognized, however, that the principles articulated in this standard also have broaderapplication to business data and operational data generally. It is also recognized thatthe data addressed by this standard is subject to data administration, metadatamanagement, records management, and other processes applied at the enterpriselevel, and that these principles must be applied in that enterprise context.

Data has many purposes, including stating requirements, providing proof ofachievement, establishing a basis for long-term product support, and many others.

Deliverable data (customer-accessible information) represents only a small fraction ofthe project data. In general, a vast amount of design, development, fabrication, andmanufacturing data remains the intellectual property of the developer/producer. Further,the value of data is not limited to its use in support of a particular product: data mayhave a life cycle longer than that of the product it describes. For instance, data fromprevious projects forms part of the foundation for new product and process design. Dataalso supports the enterprise in process redesign and quality. Thus data is essential tocompetitive position. An enterprise's data if not properly safeguarded.can also bemisused by a competitor to the competitor's advantage. For these reasons, data is anintegral part of an enterprise's intellectual assets and overall enterprise knowledge.