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This article explores the development and application of an automated computer-aided wargame to establish high-level capability requirements and concepts of operations for future Navy unmanned aerial vehicles and unmanned underwater vehicles. The Joint Theater Level Simulation-Global Operations serves as the modeling environment, in which a computer-aided exercise models the impact of future intelligence, surveillance, and reconnaissance assets. Automating wargame simulations permits the replication of a large-scale exercise without the continued investment of support personnel and operating units. The environment enables experimentation that provides force planners with pertinent metrics to inform decision-making.
Decisions and investments made today determine the assets and capabilities of the U.S. Navy for decades to come. The nation has many options about how best to equip, organize, supply, maintain, train, and employ our naval forces. These decisions involve large sums of money and impact our national security. Navy leadership uses simulation-based campaign analysis to measure risk for these investment options. Campaign simulations, such as the Synthetic Theater Operations Research Model (STORM), are complex models that generate enormous amounts of data. Finding causal threads and consistent trends within campaign analysis is inherently a big data problem. We outline the business and technical approach used to quantify the various investment risks for senior decision makers. Specifically, we present the managerial approach and controls used to generate studies that withstand scrutiny and maintain a strict study timeline. We then describe STORMMiner, a suite of automated postprocessing tools developed to support campaign analysis, and provide illustrative results from a notional STORM training scenario. This new approach has yielded tangible benefits. It substantially reduces the time and cost of campaign analysis studies, reveals insights that were previously difficult for analysts to detect, and improves the testing and vetting of the study. Consequently, the resulting risk assessment and recommendations are more useful to leadership. The managerial approach has also improved cooperation and coordination between the Navy and its analytic partners. History: This paper has been accepted for the special issue on Applications of Analytics and Operations Research in Big Data Analysis.
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