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Proceedings Paper

Investigating performance variability of processing, exploitation, and dissemination using a socio-technical systems analysis approach
Author(s): Jennifer Danczyk; Arthur Wollocko; Michael Farry; Martin Voshell
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Paper Abstract

Data collection processes supporting Intelligence, Surveillance, and Reconnaissance (ISR) missions have recently undergone a technological transition accomplished by investment in sensor platforms. Various agencies have made these investments to increase the resolution, duration, and quality of data collection, to provide more relevant and recent data to warfighters. However, while sensor improvements have increased the volume of high-resolution data, they often fail to improve situational awareness and actionable intelligence for the warfighter because it lacks efficient Processing, Exploitation, and Dissemination and filtering methods for mission-relevant information needs. The volume of collected ISR data often overwhelms manual and automated processes in modern analysis enterprises, resulting in underexploited data, insufficient, or lack of answers to information requests. The outcome is a significant breakdown in the analytical workflow. To cope with this data overload, many intelligence organizations have sought to re-organize their general staffing requirements and workflows to enhance team communication and coordination, with hopes of exploiting as much high-value data as possible and understanding the value of actionable intelligence well before its relevance has passed. Through this effort we have taken a scholarly approach to this problem by studying the evolution of Processing, Exploitation, and Dissemination, with a specific focus on the Army’s most recent evolutions using the Functional Resonance Analysis Method. This method investigates socio-technical processes by analyzing their intended functions and aspects to determine performance variabilities. Gaps are identified and recommendations about force structure and future R and D priorities to increase the throughput of the intelligence enterprise are discussed.

Paper Details

Date Published: 12 May 2016
PDF: 9 pages
Proc. SPIE 9831, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII, 98310O (12 May 2016); doi: 10.1117/12.2223804
Show Author Affiliations
Jennifer Danczyk, Charles River Analytics, Inc. (United States)
Arthur Wollocko, Charles River Analytics, Inc. (United States)
Michael Farry, Charles River Analytics, Inc. (United States)
Martin Voshell, Charles River Analytics, Inc. (United States)


Published in SPIE Proceedings Vol. 9831:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII
Michael A. Kolodny; Tien Pham, Editor(s)

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