Military intelligence analysis (IA) support tools are often developed using generalized models of IA that fail to take into consideration the real-world constraints put on analysts by factors such as organizational structures and cultures. IA in domains where distributed collaboration is required because direct communication and coordination is infeasible represents a challenge for generalized models of IA. This paper provides our analysis of distributed IA, which we conducted to support the design of software. We present a resulting set of capabilities that have been developed and deployed in an operational community. Our analysis approach and design focuses on extracting requirements and translating them into "design seeds," or guidelines for implementation, which are later used to verify that the resulting system meets the expressed requirements.

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Whether studying human cognition, designing new technologies, or exploring concepts such as safety and resilience, understanding decision making in natural settings is fundamental to Cognitive Systems Engineering (CSE). Across all of these, it is crucial for human factors engineers to be able to create realistic scenarios of interest that hit upon "cognitive pressure points" (Woods and Dekker, 2000) to elicit challenges and observe patterns in cognitive work. Although many converging methodologies have provided a rich ecological body of practice-based research and application, there is a shortage of research demonstrating the efficacy of scenario-based design in support of skill acquisition. Based on continuing research with a major metropolitan fire department, the current paper reports initial findings from ongoing work analysis. From a series of scenarios, patterns of coordination challenges are discussed with implications for future emergency response operations and training.

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