GEIA-HB-859-2006 Implementation Guide for Data Management (Formerly TechAmerica GEIA-HB-859)《数据管理的实施指南》.pdf

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1、GEIA ENGINEERING BULLETIN Implementation Guide for Data Management GEIA-HB-859 January 2006 GOVERNMENT ELECTRONICS AND INFORMATION TECHNOLOGY ASSOCIATION -. . . . . . . . . . . . . . . . . . . . . . - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ctl$.2AYf.8

2、 F k$.LTWMP% .%ka ISWW.4IICcI: T$*lWBiV%t kl(; they are what is done throughout the enterprise to manage the configuration of its products and maintain its data assets. CM and DM activities involve personnel from many corporate and functional groups and teams. The focus of the GEIA standards and han

3、dbooks is more on the functions that must be performed and not on who is tasked to perform them. GEIA does not endorse any specific organizational relationships. It is GEIA policy that standards and handbooks reflect methods available to each enterprise, which then determines how to allocate their r

4、esources and distribute these tasks. Any reference to how organizations are, or should be, comprised is the province of each individual enterprise. In the above CM and DM documents, any reference to specific organizational relationships are strictly for example purposes. They may illustrate typical

5、situations, but such references should not be construed as necessarily appropriate or correct for any given enterprise. vii Copyright Government Electronics as a result of changes in acquisition (performance- based contracts, capabilities-based acquisition, and contracted logistics support), only mi

6、nimal data may be physically delivered to the customer. Suppliers may build, operate, and maintain the system for its useful life. When data are delivered to the customer, delivery is frequently via electronic access to supplier-maintained information systems. The DM standards must recognize this ne

7、w business environment and allow for the transition from the traditional to newer acquisition approaches and new information delivery methods. To accommodate the range of acquisition approaches, ANSIIGEIA-859 provides the underlying principles of effective data management to be applied in traditiona

8、l, transitional, or new DM environments. The principles are as follows: 1. Define the enterprise relevant scope of data management 2. Plan for, acquire, and provide data responsive to customer requirements 3. Develop DM processes to fit the context and business environment in which they will be perf

9、ormed 1 Copyright Government Electronics they apply to traditional paper-based delivery of data, to electronically maintained and delivered data, and to performance-based acquisition, including contractor logistics. 1 .I Data Management Overview -shows, at the highest level of abstraction, the DM pr

10、ocess in a complex engineering program environment. The process begins when a complex engineering program is contemplated-specifically, when the requirements for the engineered product are being developed. At this time, the customer for the product plans for the product and its maintenance, the evol

11、ution of its systems to read and use the data provided by the supplier, and the measures needed to ensure that both product development and data proceed according to plan. The DM process uses the inputs, facilitators, and good data management practices to deliver all needed outputs within constraint

12、s. 2 Copyright Government Electronics or available for access when ne,eded *DM performance measured and continuously im oroved *Data archived/disposed per plan .a* I *Le 5 s ns le a rn e d *Program image enhanced; user support / improved .+ :h., 3 1 MECHANISMS/ FA CIL ITA TORS Figure i -2 is a high-

13、level depiction of DM activities. To be successful, the data manager must plan and manage the DM program, determine what data are needed by whom and when, acquire and provide stewardship over the data, and deliver, provide access to, and properly dispose of the data. 3 Copyright Government Electroni

14、cs often, customers bought more data than needed due to an inability to predict specifically and in detail what types of data would be needed. Due to acquisition reform and the explosion in information systems and networks that facilitate data sharing between customer and supplier, this approach is

15、no longer effective. 1.2 Benefits of Enterprise Data Management By conducting DM activities according to the principles of ANSIIGEIA-859, enterprises reduce the risk of not having needed data available when and where they are needed. Having the right data available supports better design and develop

16、ment decisions, supports faster decision processes, provides early-warning information, and reduces costs associated with hard-copy data delivery. Providing electronic access to the authoritative source for a given data product, for example, ensures data integrity in a way not possible in the old en

17、vironment where multiple hard-copy documents were delivered over the life cycle. The enterprise DM process, aided by new computing and networking support, makes information available more quickly and facilitates collaboration among customers and suppliers. It controls the digital format and the proc

18、edures necessary to exchange, index, store, and distribute or provide access to data. It offers a wide range of benefits that contribute to improvements in the cost, schedule, performance, and support of complex engineered systems. 4 Copyright Government Electronics the context the photos provide ha

19、s helped reduce errors in assembly. By having a DM strategic plan that includes a gradual transition to an integrated DM infrastructure, and a vision of how DM can be used across the enterprise, this data manager enabled a no-cost improvement to the circuit board assembly function. This data manager

20、s DM strategic plan includes transition to an integrated DM and configuration management (CM) architecture as his next phase. 5 Copyright Government Electronics strategic DM planning may also take place at this time. 2.3 Data Management Process Description Figure 4 -1, provides an overview of the DM

21、 process (showing the entire process as a single activity) with the following components: + Inputs-information needed to initiate and perform the process + Constraints-information or factors that inhibit or put limitations on the process + Mechanisms/facilitators-information, tools, methods, and tec

22、hnologies that enable or enhance the process + Outputs-results that derive from the process and information provided by the proces s. The Defense Acquisition Guidebook, a compilation of best practices for use in DoD acquisition programs, states the requirement for data management, as follows: Data M

23、anagement plays an important role in the systems engineering process. In the program office, data management consists of the disciplined processes and systems used to plan for, acquire, access, manage, protect, and use data of a technical nature to support the total life cycle of the system. Under t

24、he Total Life Cycle Systems Management concept, the program manager is responsible for Data Management. The program manager should develop a plan for managing defense system data during each phase of the system life cycle and include it in the Systems Engineering Plan. Data Management applies polici

25、es, systems, and procedures to identify and control data requirements; to responsively and economically acquire, access, and distribute data; and to analyze data use. Adherence to data management principles enables the sharing, integration, and management of data by government and industry, and ensu

26、res that data products (information) meet or exceed customer requirements. Recent government and industry initiatives in Data Management have changed the approach and scope of data management, and made it a stronger element in the systems engineering process. 0 Data Management has a leading role in

27、capturing, organizing, and providing information for the following uses in the systems engineering process: Enabling collaboration and life cycle use of acquisition system product data; 0 7 Copyright Government Electronics Providing data correlation and traceability among requirements, designs, solu

28、tions, decision, and rationale; Documenting engineering decisions, including procedures, methods, results, and analyses; Functioning as a reference and support tool for the systems engineering effort and process; Facilitating technology insertion for affordability improvements during re- procurement

29、 and post-production support; and Supporting configuration procedures, as needed. 0 0 0 0 0 Here and elsewhere, DoD policy provides a broad scope to data management: + It relates to the complete program life cycle (i.e., supporting the systems engineering effort; interacting with program management,

30、 configuration management, and business management; and providing information for operational support of deployed systems). + It embraces the use of contractor data formats, whenever feasible. + It reflects the integration of data management with all program functional activities. + It does not limi

31、t the data to be managed solely to contractually specified data but encompasses government programmatic information, as well. Current policy recognizes the reality that in todays environment, most data exist in digital format; the challenge is to find the most efficient and cost-effective mode of de

32、livery (submittal or access) from the data source that supports the product throughout its life cycle. The DM process detailed in this handbook encompasses all data generated as part of the acquisition, development, production, and support of products and services. It involves customer and supplier

33、activities, and it embraces acquisition reforms and integrated product and process development teams. Data management, as a discipline that cuts across all functional activities of a program, can and must provide the unifying focus on the goal of an integrated data environment. 2.3.1 Description of

34、Top-Level Data Management Activities As shown in w, the DM process has four top-level activities: plan and manage data, analyze data needs, acquire and control data, and access data. They are described below in terms of their inputs, outputs, constraints, and facilitators. The need to perform the DM

35、 activities is independent of any specific organizational structure or specific method. Defense Acquisition Guidebook, Chapter 4 1 8 Copyright Government Electronics j.mI, Acquisition and Preparation, and Section 5, Data Asset Control. + Inputs * Program plan and schedule. This input aligns data sub

36、mittal and access requirements with the final version of the program planning and scheduling. * Data provider s proposal. This input represents the providers formal proposal submittal. It is a basis for proposal evaluation and the modification of data requirements to accommodate accepted value-addin

37、g alternate approaches. * Data submitted by the data provider. This input represents the data generated and supplied under the terms of the contract. + outputs * Contract data requirements. This output represents the list of required data after negotiation. * Data products. This output represents th

38、e data produced in response to the list of data required and the SOW or SOO. * Access rules. This output represents the rules for access associated with each data product. * Data status. This output provides performance information and, in conjunction with the access rules, is a factor in determinin

39、g authorized access. + Constraints * CONOPS or equivalent information concerning the enterprise infrastructure. This constraint limits the data interchange method. 11 Copyright Government Electronics it is intended as a short introduction to DM strategic planning. If the enterprise has a process for

40、 strategic planning, it should be used. Other enterprise planning models can be adapted for strategic planning as well. In addition, numerous reference materials, courses, and the like are available on this topic. 3.3.2.1 Summary The process begins by identifying the vision and mission of the DM eff

41、ort (either for the enterprises DM organization or for a specific program or contract). Once the vision and mission are clearly defined, the DM organization conducts a series of analyses (for example, external environment analysis, internal environment analysis, current versus proposed gap, and benc

42、hmarking), which provide a context for identifying the DM strategic issues. Strategic programming follows; the DM organization develops specific strategies, including goals, action plans, and tactics. Periodically, the organization evaluates its strategies and reviews its strategic plan, considering

43、 progress made and evolving changes. It may take several planning iterations before strategic planning becomes institutionalized and organizations learn to think strategically. 3.3.2.2 Develop Vision and Mission Identification of the DM vision and mission is the first step of any strategic planning

44、process. The vision sets out the reasons for the DM effort and the state that the organization aims to achieve; it enables development of goals and performance objectives. Both the vision and mission are defined within the framework of the enterprise culture and contract constraints and are used as

45、a context for development and evaluation of strategies. One cannot overemphasize the importance of a clear vision and mission; none of the subsequent steps will matter if the organization is not certain where it is headed. The data manager must do some creative thinking to develop the DM organizatio

46、ns vision and mission. Thinking beyond what the DM organization must do to satisfy contractual requirements, the data manager should consider what else data management can do for the enterprise. A strategic vision can be developed via brainstorming, facilitated working groups, or some other means to

47、 spur thinking beyond what is already known. The results of out-of- the-box thinking will be tempered later by real-world constraints, such as resources, contractual restrictions, and the like; but the first step is to think creatively about how data management can best benefit the enterprise and it

48、s customers. 16 Copyright Government Electronics a proven technique is a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis. In short, a SWOT analysis addresses internal factors such as enterprise policies affecting DM: functions such as the configuration management, quality assurance

49、, and records management operations; and available resources such as staff, IT, and communications. In the SWOT technique, one also analyzes information about the external environment; including economic, legal, technological, political, and international factors, the customer base, and the state of the industry. SWOT analysis identifies factors that may affect desired future outcomes of the organization. The SWOT model is based on identifying the organizations internal strengths and weaknesses, opportunities for improvement, and threats of the external environment; and consequently