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Networks in Organizational Risk Management

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NAS2-03118
Agency Tracking Number: 022607
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
12 Gill Street, Ste 1400
Woburn, MA 01801
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Kari Chopra
 (781) 496-2312
Business Contact
 Margaret Clancy
Title: Business Official
Phone: (781) 496-2415
Research Institution

We propose to develop a formal modeling tool, Networks in Organizational Risk Management (NORM), that allows mission planners and organizational designers to create and experiment with organizational structures that minimize risk throughout the lifecycle of a system. The core of our approach is a model of the network of interrelationships among people, knowledge, tasks, technology, organizational goals, system failures, and the surrounding environment. Our proposal is uniquely innovative in three respects. First, we seek to develop a formal quantitative model of organizational risk management rather than qualitative descriptions of theoretical aspects or recommended practices. Second, our model encapsulates a holistic view of organizational risk management, where organizations are not depicted solely as a source of errors but also as a means for detecting and responding to system failures. Finally, in contrast to conventional methods that focus on analyzing technical failures in the system, our model incorporates explicit measures of organizational phenomena such as goals, decisions, authority, communication, and informal social networks. The software tool we envision will provide capabilities for simulation, to allow mission planners to experiment with ?what-if? scenarios and optimization to generate organizational designs that minimize the losses incurred by system failures.

* Information listed above is at the time of submission. *

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