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The U.S. Air Force is consistently evolving to support current and future operations through the planning and execution
of intelligence, surveillance and reconnaissance (ISR) missions. However, it is a challenge to maintain a precise
awareness of current and emerging ISR capabilities to properly prepare for future conflicts. We present a decisionsupport
tool for acquisition managers to empirically compare ISR capabilities and approaches to employing them,
thereby enabling the DoD to acquire ISR platforms and sensors that provide the greatest return on investment. We have
developed an analysis environment to perform modeling and simulation-based experiments to objectively compare
alternatives. First, the analyst specifies an operational scenario for an area of operations by providing terrain and threat
information; a set of nominated collections; sensor and platform capabilities; and processing, exploitation, and
dissemination (PED) capacities. Next, the analyst selects and configures ISR collection strategies to generate collection
plans. The analyst then defines customizable measures of effectiveness or performance to compute during the
experiment. Finally, the analyst empirically compares the efficacy of each solution and generates concise reports to
document their conclusions, providing traceable evidence for acquisition decisions. Our capability demonstrates the
utility of using a workbench environment for analysts to design and run experiments. Crafting impartial metrics enables
the acquisition manager to focus on evaluating solutions based on specific military needs. Finally, the metric and
collection plan visualizations provide an intuitive understanding of the suitability of particular solutions. This facilitates
a more agile acquisition strategy that handles rapidly changing technology in response to current military needs.
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