Technical Report
WRT 1014: Foundations for a Model-Based Portfolio Analysis Capability for the Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense (JPEO-CBRND)
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Enterprises and System of Systems
Report Number: SERC-2020-TR-013
Publication Date: 2020-06-12
Project:
Foundations for a Model-Based Portfolio Analysis Capability for the Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense (JPEO-CBRND)
Principal Investigators:
Dr. Daniel DeLaurentis
Co-Principal Investigators:
Dr. Cesare Guariniello
This research effort identified the needs of JPEO‐CBRND and provided initial directions towards the establishment and utilization of a portfolio analysis capability. This capability would support decisions for the most advantageous investments across the whole enterprise. The work has been articulated in two phases: a first one of knowledge and discovery, for the team to get acquainted with the needs of JPEO‐CBRND, and the second one to model some of these needs and to begin the development of a prototype computational tool for enterprise decision‐making. Both phases leveraged previous experience, including the successful SERC workshop on Modular Open Systems Approach (MOSA) in 2017 and the SERC‐developed System of Systems Analytic Workbench (AWB), with its family of analysis and synthesis tools that have direct relevance to the JPEO‐CBRND need for enterprise portfolio analysis. A workshop where the team had the opportunity to meet a large group of potential users of this research was extremely valuable in defining short‐term and long‐term needs of JPEO‐CBRND. Frequent interaction with engineers from JPEO‐CBRND supported the identification of multiple Systems Engineering and System‐of‐Systems Engineering methodologies that are appropriate to address the identified needs. Some of the methodologies have been applied to a case study of interest to JPEO‐CBRND to show what type of information is necessary to inform appropriate methods to generate the heuristically driven decision‐making support.