A systems approach to risk management through leading safety indicators

The goal of leading indicators for safety is to identify the potential for an accident before it occurs. Past efforts have focused on identifying general leading indicators, such as maintenance backlog, that apply widely in an industry or even across industries. Other recommendations produce more system-specific leading indicators, but start from system hazard analysis and thus are limited by the causes considered by the traditional hazard analysis techniques. Most rely on quantitative metrics, often based on probabilistic risk assessments. This paper describes a new and different approach to identifying system-specific leading indicators and provides guidance in designing a risk management structure to generate, monitor and use the results. The approach is based on the STAMP (System-Theoretic Accident Model and Processes) model of accident causation and tools that have been designed to build on that model. STAMP extends current accident causality to include more complex causes than simply component failures and chains of failure events or deviations from operational expectations. It incorporates basic principles of systems thinking and is based on systems theory rather than traditional reliability theory.

[1]  Qi D. Van Eikema Hommes,et al.  System theoretic approach for determining causal factors of quality loss in complex system design , 2014 .

[2]  Joe T Kretchik Process safety management of highly hazardous chemicals , 2000 .

[3]  Mark Manion,et al.  The epistemology of fault tree analysis: an ethical critique , 2007 .

[4]  Ingrid Bouwer Utne,et al.  Building Safety indicators: Part 2 - Application, practices and results , 2011 .

[5]  Ioannis M. Dokas,et al.  EWaSAP: An early warning sign identification approach based on a systemic hazard analysis , 2013 .

[6]  P. Slovic,et al.  FACTS AND FEARS: UNDERSTANDING PERCEIVED RISK.: P/3 , 1980 .

[7]  J P Bagian THE OPPORTUNITY OF PRECURSORS. IN: ACCIDENT PRECURSOR ANALYSIS AND MANAGEMENT: REDUCING TECHNOLOGICAL RISK THROUGH DILIGENCE , 2004 .

[8]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[9]  T. W. van der Schaaf,et al.  CHECKING FOR BIASES IN INCIDENT REPORTING. IN: ACCIDENT PRECURSOR ANALYSIS AND MANAGEMENT: REDUCING TECHNOLOGICAL RISK THROUGH DILIGENCE , 2004 .

[10]  Kathryn Mearns,et al.  Measuring safety climate: identifying the common features☆ , 2000 .

[11]  Joel Cutcher-Gershenfeld,et al.  Modeling, Analyzing, and Engineering NASA's Safety Culture , 2005 .

[12]  John A. McDermid,et al.  The science and superstition of quantitative risk assessment , 2012 .

[13]  Daniel Kahneman,et al.  Availability: A heuristic for judging frequency and probability , 1973 .

[14]  Petter Grytten Almklov,et al.  Organisational safety indicators: Some conceptual considerations and a supplementary qualitative approach , 2010 .

[15]  D M Murphy,et al.  The SAM framework: modeling the effects of management factors on human behavior in risk analysis. , 1996, Risk analysis : an official publication of the Society for Risk Analysis.

[16]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[17]  Nancy G. Leveson Intent Specifications: An Approach to Building Human-Centered Specifications , 2000, IEEE Trans. Software Eng..

[18]  M Tamuz UNDERSTANDING ACCIDENT PRECURSORS. IN: ACCIDENT PRECURSOR ANALYSIS AND MANAGEMENT: REDUCING TECHNOLOGICAL RISK THROUGH DILIGENCE , 2004 .

[19]  Patrick T. W. Hudson,et al.  Process indicators : Managing safety by the numbers , 2009 .

[20]  Ingrid Bouwer Utne,et al.  Building Safety indicators: Part 1 – Theoretical foundation , 2011 .

[21]  Ioannis A. Papazoglou,et al.  Modeling accidents for prioritizing prevention , 2007, Reliab. Eng. Syst. Saf..

[22]  Vicki M. Bier,et al.  Accident Precursor Analysis and Management: Reducing Technological Risk Through Diligence , 2004 .

[23]  B. Fischhoff,et al.  Facts and Fears: Understanding Perceived Risk , 2005 .

[24]  Ibrahim A. Khawaji Developing system-based leading indicators for proactive risk management in the chemical processing industry , 2012 .

[25]  A. Tversky,et al.  On the psychology of prediction , 1973 .

[26]  Ronald J. Willey Layer of Protection Analysis , 2014 .

[27]  Jens Rasmussen,et al.  Risk management in a dynamic society: a modelling problem , 1997 .

[28]  W. D. Rowe,et al.  Risk Assessment Review Group Report to the U. S. Nuclear Regulatory Commission , 1979, IEEE Transactions on Nuclear Science.

[29]  L Lisette Kanse,et al.  Checking for biases in incident reporting , 2001 .

[30]  Kim Jennings,et al.  Guidance on developing safety performance indicators , 2009 .

[31]  M E Paté-Cornell,et al.  Warning systems in risk management. , 1986, Risk analysis : an official publication of the Society for Risk Analysis.

[32]  W R Corcoran DEFINING AND ANALYZING PRECURSORS. IN: ACCIDENT PRECURSOR ANALYSIS AND MANAGEMENT: REDUCING TECHNOLOGICAL RISK THROUGH DILIGENCE , 2004 .

[33]  John Pruitt,et al.  Deepwater Bop Control Systems - A Look At Reliability Issues , 2003 .

[34]  Jaleh Samadi,et al.  Development of a systemic risk management approach for CO2 capture, transport and storage projects , 2012 .

[35]  John M. Carroll,et al.  Modeling, analyzing, and engineeering safety culture , 2005 .

[36]  Nancy G. Leveson,et al.  A new accident model for engineering safer systems , 2004 .