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Decoding Data Science

The U.S. Coast Guard's Evolving Needs and Their Implications

by Aaron C. Davenport, Michelle D. Ziegler, Abbie Tingstad, Katherine Anania, Daniel Ish, Nidhi Kalra, Scott Savitz, Rachel Liang, Melissa Bauman

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Like many large organizations, the U.S. Coast Guard has vast amounts of data that it could use to identify, predict, and solve pressing challenges. Data science could be valuable to the Coast Guard in a variety of domains, such as forecasting the resources needed for future trends in search-and-rescue missions, further automating aids to navigation, or automating fishery observations. In personnel areas, data science could help improve billet assignments, determine where to focus recruiting efforts, and boost employee retention.

The Coast Guard has an opportunity to plot the path to determine service-specific uses, identify the strategy and driving mechanisms, and begin laying out a plan for the use of data science, which includes data collection, analysis, and management; artificial intelligence; and machine learning. This Perspective outlines the role that data science can play in decisionmaking processes and provides a selected set of key questions and sensitivities for the Coast Guard to consider in developing its future usage of data science.

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This research was sponsored by the U.S. Coast Guard Office of Emerging Policy and conducted within the Strategy, Policy and Operations Program of the Homeland Security Operational Analysis Center (HSOAC).

This publication is part of the RAND Corporation Perspective series. RAND Perspectives present expert insights on timely policy issues. All RAND Perspectives undergo peer review to ensure high standards for quality and objectivity.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.