Toward monitoring organizational safety indicators by integrating probabilistic risk assessment, socio-technical systems theory, and big data analytics

Justin Pence, Zahra Mohaghegh, Cheri Ostroff, Ernie Kee, Fatma Yilmaz, Rick Grantom, David Johnson

Research output: Contribution to conferencePaper

Abstract

Many catastrophic accidents have organizational factors as key contributors; however, current generations of Probabilistic Risk Assessment (PRA) do not include a comprehensive representation of the underlying organizational failure mechanisms. This paper reports on the current status of new research with the idealistic goal of monitoring organizational safety indicators. Because of the evolving nature of computational power and information-sharing technologies, 'Internet of Things' has been adopted as a metaphor to describe the authors' vision for combining multiple levels of organizational analysis into a real-time application for monitoring the changing landscape of risk. The short-term objectives are: (1) identifying the organizational root causes of failure and their paths of influence on technical system performance, utilizing theoretical models of social phenomena, (2) quantifying the models using advanced measurement and predictive methodologies, big data analytics, and uncertainty analysis, and (3) proposing preventive approaches. Socio-Technical risk analysis deals with wide-ranging, incomplete, and unstructured data. Therefore, this research focuses on developing hybrid predictive technologies for PRA that are not only grounded on Socio-Technical Systems theory, but also serve to expand the classical approach of data extraction and execution for risk analysis by incorporating techniques such as text mining, network data analytics, and data curation.

Original languageEnglish (US)
StatePublished - Jan 1 2014
Event12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014 - Honolulu, United States
Duration: Jun 22 2014Jun 27 2014

Other

Other12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014
CountryUnited States
CityHonolulu
Period6/22/146/27/14

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Keywords

  • Big data
  • Organizational safety indicators
  • Probabilistic risk assessment
  • Real-time safety monitoring
  • Socio-technical risk analysis

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

Cite this

Pence, J., Mohaghegh, Z., Ostroff, C., Kee, E., Yilmaz, F., Grantom, R., & Johnson, D. (2014). Toward monitoring organizational safety indicators by integrating probabilistic risk assessment, socio-technical systems theory, and big data analytics. Paper presented at 12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014, Honolulu, United States.