1. The Enterprise Relevant Scope of DM
Module P1

2. Learning Objectives and Outcome
Understand how DM principles apply to enterprise data that was not traditionally placed under DM
Understand how DM can support the enterprise as a whole
Learning Outcome:
Leverage program or project DM to support many customers in the enterprise

3. Customers of the DM Function
Program and project data and data products support many customers across the enterprise, and outside the enterprise
Enterprise
Finance
Human
Resources
Legal
Well-managed
Data repository
Presentation: Notional graphic above
The graphic above is a raw draft to illustrate the number of users within and outside the enterprise. SMEs can supply many more, if the graphic is presented another way (pop window, and gradually add each in, with an explanation of what information each exchanges with the DM function.)
Explanatory Material:
In addition to providing data products for delivery up the project/program management chain, well-managed data supports planning and analyses by other organizations.
Good DM will support not only ‘decision provenance’ (the ability to retrieve the business context of prior decisions) but trend analyses by Finance, HR and others to provide better support to the program.
In addition, customers external to the enterprise (regulatory bodies, auditors, etc.) are well-served, and the enterprise benefits from this improved relationship.
References:
Introduction, Scope and Terminology sections
Project and program data: Principles 2 and 4
Contract
Management
Program
Management
Suppliers
Engineering
Product
Configuration
Management
Partners

4. DM: An Enterprise Business Process
Data management principles should be applied to many types of data throughout the enterprise
Table 1. Types of Data
Type
Usage
Examples
Product
Collaboration
Cost, schedule, and performance data
Scientific data such as written notes and observation of phenomena
Engineering drawings and models, parts catalogs, software applications and their components, operational and maintenance instructions, and training materials
Business
Plans and schedules, financial information, inventory status, and human resource information
Operational
Transactional records exchange
Orders, issues, receipts, bills of lading, and invoices
Presentation:
The table is directly from the standard. It could be presented more dynamically/artistically.
Explanatory material:
Paraphrased from GEIA 859 -Foreword, :
Good data management identifies, defines, prepares, controls, archives, and disposes of data—and it requires investments in labor, supporting systems, and time. This standard should be used to provide consistent, high-quality data management (DM) to ensure that the enterprise reaps a return on this investment. When DM principles are applied using effective practices, the return on the investment in data is maximized and product life-cycle costs are reduced. This standard is intended to be used when establishing, performing, or evaluating DM processes in any industry, business enterprise, or governmental enterprise.
Data management is a discipline that plans for, acquires, and stewards product and product-related business data, throughout the product and data life cycles. Thus, this standard primarily addresses product data and the business data intrinsic to collaboration during product acquisition and sustainment. However, the principles articulated in this standard also have broader application to business data and operational data generally.
References:
Introduction, Scope section
Principle 1

5. Shift in Tasks Performed
Traditional
Identification and definition
Acquisition and preparation
Control
Disposition
Archiving
Tasks required in 859
DM strategy and architecture development
DM process and infrastructure design
DM execution
DM process and infrastructure maintenance
Presentation:
Explanatory Material:
Although these functions remain valid for DM, they are no longer a sufficient response to contemporary DM needs. However, there are DM “pockets of excellence” in particular firms and agencies that have addressed the broader foundations of DM. Further, there has been some success in documenting contemporary methods in specific organizations, in the software engineering capability maturity model (CMM), and in the requirements for International Organization for Standardization (ISO) 9000 certification. None of these, however, has yet brought a unifying, strategic focus to DM. The intent of this standard is to highlight the importance of the strategic DM and supporting infrastructure. Accordingly, GEIA Standard 859 defines a set of four higher-level DM tasks
References: Table 1-2 for additional information on new tasks, subtasks, and needed skills
Transforming from clerk or librarian to an enterprise enabler!

6. New skills needed Budgeting Cost benefit analysis
Strategic planning and management
Legal
Electronic data administration
Process design and engineering
Knowledge management
Software engineering
Presentation
Explanatory Material
The new tasks require skills that have not previously been demanded of data managers. It should be abundantly clear that most of the skills are not resident in existing DM enterprises, and probably will not be because of the diversity of enterprises. In a rapidly changing technological society, it is crucial to train and continuously improve the resources (people, processes, tools, budgets) that support one of an enterprise’s most valuable assets, data. DM is functionally responsible for ensuring that the integrity and accessibility of data are consistent with the users’ requirements. The data manager, to be effective, should be provided the opportunity to achieve expertise through training, experience, and mentoring. Areas of concentration include planning, acquisition, preparation, control, disposition, archiving, and communication.
Reference Table 1-2 for additional information on new tasks, subtasks, and needed skills

7. Quiz Questions – Module P1
Who are customers for Program Data Management:
a. PMO
b. CM
c. Finance
d. Government Accountability Office (GAO)
e. All of the above
What data can be managed in accordance with Standard 859?
a. Engineering drawings
b. Scientific data
c. Plans, schedules, inventory status
d. Human Resources data