- How can data collection be benchmarked and used in large, complex commercial enterprises — in particular, advanced data science techniques and analytics?
- What lessons are applicable to the DoD acquisition data and analytics environment, and how can DoD acquisition analytics capabilities be improved?
Public and private organizations are increasingly aware of the potential value of data and analytics to improving organizational performance and outcomes. The U.S. Department of Defense (DoD) is one of those organizations. Its size, complexity, security needs, and culture have created a challenging environment for successful use of data in decisionmaking. DoD's acquisition data lay an important part of the foundation for decisions about weapon systems. Because the private sector faces similar data challenges, the authors examined commercial data practices that might translate to the DoD acquisition community in the areas of data governance and analytics. Benchmarking select private-sector data governance and analytics practices helps establish a baseline against which DoD practices can be compared. That comparison can be used to identify areas in which DoD could improve and suggests actions or approaches to make those improvements. The authors determined that functions associated with the office of a chief data officer and associated data governance and data management are foundational requirements to pursue an analytics strategy in any organization.
- There is a broad consensus on data governance and analytics guiding principles (i.e., lessons in creating a data-focused organization).
- Data governance and strategy are critical enablers of analytics capability. Emphasis should be on how analytics contributes to an organization's strategic goals.
- Organizational design should be federated: a strong central chief data officer with core governance and analytics function and distributed analytics capabilities within business units.
- Resource requirements for analytics vary widely and are driven by strategic objectives and tailored to where an organization starts (i.e., existing data analytics capabilities).
- Approach implementation using change management strategies. Becoming a data-driven organization was viewed as a transformative change in business processes.
- Data and analytics maturity models reflect commercial benchmarks and provide a road map for improving analytics capabilities.
- Because data governance and strategy are critical enablers of analytics capability, the Principal Deputy Assistant Secretary of Defense, Acquisition Enablers (PDASD[AE]) should create and maintain a data governance and analytics strategy for acquisition.
- PDASD(AE) should use its position to expand its role in data governance, management, and analytics specific to acquisition to further improve the federated organizational design. This could include expanding the existing Acquisition Visibility Steering Group and Working Group to include analytics.
- DoD leadership needs to see that resources are being spent efficiently. Demonstrating value quickly through the use of analytics activities to help solve or bring clarity to a pressing issue for the organization is one way to justify use of resources for analytics.
- Further maturing the data analytics capability within the DoD acquisition community would be transformative and may require changes or impacts in decisionmaking processes, business processes, organizational structure, and organizational culture.
- The acquisition community within the Office of the Under Secretary of Defense for Acquisition and Sustainment should continue to build on and leverage existing infrastructure, the common data framework for program information, and existing analytics capability.