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Title: Using Enterprise Architecture for Analysis of a Complex Adaptive Organization's Risk Inducing Characteristics

Abstract

Sandia National Laboratories is an organization with a wide range of research and development activities that include nuclear, explosives, and chemical hazards. In addition, Sandia has over 2000 labs and over 40 major test facilities, such as the Thermal Test Complex, the Lightning Test Facility, and the Rocket Sled Track. In order to support safe operations, Sandia has a diverse Environment, Safety, and Health (ES&H) organization that provides expertise to support engineers and scientists in performing work safely. With such a diverse organization to support, the ES&H program continuously seeks opportunities to improve the services provided for Sandia by using various methods as part of their risk management strategy. One of the methods being investigated is using enterprise architecture analysis to mitigate risk inducing characteristics such as normalization of deviance, organizational drift, and problems in information flow. This paper is a case study for how a Department of Defense Architecture Framework (DoDAF) model of the ES&H enterprise, including information technology applications, can be analyzed to understand the level of risk associated with the risk inducing characteristics discussed above. While the analysis is not complete, we provide proposed analysis methods that will be used for future research as the project progresses.

Authors:
 [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1429823
Report Number(s):
SAND-2017-8317J
655974
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Program Document
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS

Citation Formats

Salguero, Laura Marie, Huff, Johnathon, Matta, Anthony R., and Collins, Sue S. Using Enterprise Architecture for Analysis of a Complex Adaptive Organization's Risk Inducing Characteristics. United States: N. p., 2017. Web.
Salguero, Laura Marie, Huff, Johnathon, Matta, Anthony R., & Collins, Sue S. Using Enterprise Architecture for Analysis of a Complex Adaptive Organization's Risk Inducing Characteristics. United States.
Salguero, Laura Marie, Huff, Johnathon, Matta, Anthony R., and Collins, Sue S. Tue . "Using Enterprise Architecture for Analysis of a Complex Adaptive Organization's Risk Inducing Characteristics". United States.
@article{osti_1429823,
title = {Using Enterprise Architecture for Analysis of a Complex Adaptive Organization's Risk Inducing Characteristics},
author = {Salguero, Laura Marie and Huff, Johnathon and Matta, Anthony R. and Collins, Sue S.},
abstractNote = {Sandia National Laboratories is an organization with a wide range of research and development activities that include nuclear, explosives, and chemical hazards. In addition, Sandia has over 2000 labs and over 40 major test facilities, such as the Thermal Test Complex, the Lightning Test Facility, and the Rocket Sled Track. In order to support safe operations, Sandia has a diverse Environment, Safety, and Health (ES&H) organization that provides expertise to support engineers and scientists in performing work safely. With such a diverse organization to support, the ES&H program continuously seeks opportunities to improve the services provided for Sandia by using various methods as part of their risk management strategy. One of the methods being investigated is using enterprise architecture analysis to mitigate risk inducing characteristics such as normalization of deviance, organizational drift, and problems in information flow. This paper is a case study for how a Department of Defense Architecture Framework (DoDAF) model of the ES&H enterprise, including information technology applications, can be analyzed to understand the level of risk associated with the risk inducing characteristics discussed above. While the analysis is not complete, we provide proposed analysis methods that will be used for future research as the project progresses.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {8}
}

Program Document:
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