CESG Connections Magazine 2020 Issue | Page 12

National Defense Strategy THE DATA IMPERATIVE IN AN ERA OF GREAT POWER COMPETITION An issue Analysis by GREAT POWER competition—not terrorism—has reemerged as the central challenge to U.S. national security. China’s and Russia’s military modernization initiatives are eroding the Department of Defense’s (DoD’s) conventional deterrent. The 2018 National Defense Strategy (NDS) addresses this problem by directing DoD to ensure the Armed Forces are sufficiently lethal to effectively deter Chinese or Russian aggression against U.S. interests. By its own admission, DoD must change the way it conducts its business to do so. Making resource tradeoffs is no longer an aspirational goal for DoD—it’s an imperative. Aligning resources with priorities is particularly challenging for large bureaucracies. If DoD were its own nation, it would rank in the top 20 countries by GDP, with an annual budget of over $700 billion. Its sheer scale makes change of any kind—let alone a strategic reorientation—exceedingly difficult. DoD’s ability to make the necessary resource tradeoffs to execute the NDS depends on data—data that allows DoD 12 • CESGovernment.com leaders to measure lethality, performance, innovation, and affordability. It is this data that illuminates the path forward by shedding light on the choices confronting DoD along with the implications and consequences of each. Top Pentagon leaders are striving to find ways to leverage data and glean valuable insights for their missions despite siloed organizational functions and datasets. Non-interoperable data schemas from multiple disparate systems lack common elements and formats, which makes integration difficult. To accomplish this integration, DoD must leverage ever-expanding volumes of data within these silos to create decision-grade information. Accomplishing this enables data-driven analysis to inform strategy and planning amid resource tradeoff decisions. Govini, an Arlington-based data and analytics firm, leverages cutting-edge data science and machine learning technologies as well as an expansive dataset to assist