Research Summaries

Back Big Data Elevation of Supply Chain Vulnerabilities

Fiscal Year 2018
Division Research & Sponsored Programs
Department Naval Research Program
Investigator(s) Gallup, Shelley P.
Wood, Brian P.
Irvine, Cynthia E.
MacKinnon, Douglas J.
Zhao, Ying
Sponsor NPS Naval Research Program (Navy)
Summary Big Data analysis has produced holistic insights into relationships that were never previously discerned. Using Big Data systems like IBM Watson can find critical vulnerabilities in the supply chain that may not be apparent. Supply chains face increasing liabilities from cyber weaknesses to small vendor financial exposure. Finding and correcting critical weaknesses provides significant resiliency during major combat operations or humanitarian operations while increasing the efficiently across all ranges of military operations. We seek to focus Big Data methods and applications on critical supply chains like SPY radar systems and F-35 systems to find unseen relationships. We also seek to use Big Data methodologies to find small critical vendors that may discontinue operations due to financial exposure, liabilities, or perhaps criminal activity and to find additional or alternative sources of supply for critical systems. Department of Defense (DoD) datasets have been analyzed through implementation of Lexical Link Analysis (LLA) to understand how requirements language structure, specific requirements language, and underlying requirements language themes or patterns, may identify successful systems. Ultimately, this effort may help identify pitfalls in program development and mitigate the need for costly requirements changes/updates, potentially speeding system delivery, lowering cost, and providing the correct capability to the end users.
Keywords
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal