Elsevier

Safety Science

Volume 51, Issue 1, January 2013, Pages 187-201
Safety Science

Outlines of a sensitising model for industrial safety assessment

https://doi.org/10.1016/j.ssci.2012.06.008Get rights and content

Abstract

This paper introduces what is defined as a sensitising model. This model has been developed to support empirical and methodological research and studies in different high-risk industries. Its purpose is to assist current and future practices of industrial safety assessments by taking into account input from the social sciences, reflecting in particular their insights on major accidents. For this purpose, the first objective of this paper is to take an overall view. There is not, in principle, only one way of introducing social sciences into safety assessment practices. In a historical approach four research traditions (safety management system, safety culture, high-reliability organisations, accident investigations and models) are introduced. A classification scheme is produced to make sense of the diversity of traditions according to three dimensions. It is argued that an integration of all the different research traditions would not be realistic. However, it is explained that some models offer complementary features worth exploring. The second objective of this paper is thus to present the design rationale of such an exploration in order to produce a sensitising model for safety assessments. This model is obtained by combining two generic models from the managerial and sociological (safety) literature. Safety is approached in this model as the dynamic interaction between several dimensions, including technological design and tasks, structural and functional features of organisations, but also cognitive, cultural and power issues, at several layers of analysis. Theoretical aspects with regard to the position and status of this model are discussed.

Highlights

► Future practices of industrial safety assessment should rely on the insights of social sciences. ► There is a need as a consequence to produce models reflecting these insights and it is argued that there is not one single way of doing this. ► Four different research traditions are therefore identified. ► A classification framework helps to locate them and to specify potential synergies between works in research traditions. ► A sensitising model is introduced, resulting from the combination of a normative model and a descriptive one.

Introduction

Certainly one of the most challenging tasks in safety science today is to develop ways of assessing systems in order to capture the patterns identified by social sciences following major accidents, to prevent them from causing disasters. In other words, the challenge is to develop ways to better grasp in foresight what is being interpreted in hindsight, or, as shown in Fig. 1, to move from a study of past failures (1) to an anticipation of future ones (2).

This challenge is empirical, methodological, theoretical and epistemological (Le Coze, 2011a). This paper deals more specifically with the theoretical aspect of this challenge, setting aside the empirical, methodological and epistemological ones. A recent event such as the Macondo well disaster (Chief Counsel’s Report, 2011) demonstrates again the necessity of moving beyond traditional methods and tools designed for assessing safety. So far, these have been strongly dominated by technologically and quantitatively oriented rationales (e.g. probabilistic safety assessment), with attempts to complement them from other backgrounds such as human factors (e.g. human reliability assessment). This technological and quantitative rationale can now be considered too simplistic (although certainly prerequisite for any safety approach). It does not incorporate what makes these systems so highly complex, i.e. their dynamic and systemic properties (Le Coze, 2005, Vaughan et al., 2005). Yet, the current and next generation of technological developments require enhanced abilities, both from states, public and private companies, to better anticipate technological, human, organisational and socio-cultural types of failures (Evan and Manion, 2002). This calls for a better interface between technology and social sciences and their translation into safety assessment practices.

If one wants to tackle this challenge, one has to deal with a theoretical problem: data collection and interpretation are always, whether implicitly or explicitly, and to a large extent, knowledge-driven. A safety assessment must rely on some form of indications about where to look and what to derive from observations. As a consequence, one has to specify key dimensions indicating relevant areas to be considered and investigated for safety assessment during empirical phases (Le Coze, 2011b). This issue has been clearly formulated by Bourrier and Laroche (2001, p. 49) ‘One needs to determine where to look (…) it is difficult to study the entire functioning of an organisation or a system of organisations. One has to make choices and decide to approach the organisational reality through a series of slices, perspectives and angles of observations’.

Although some authors have now started to move in this direction and provide some guidance (e.g. Berman and Ackroyd, 2006, Dalzell and Hopkins, 2006, Reimann and Pia, 2007, Reimann and Pia, 2009, Boin and Schulman, 2010), this research area still remains without a strong base. For instance, no systematic and analytical overview of models is available so far for this particular subject. Yet, this is a necessary step in clarifying different design rationales for safety assessment. The first purpose of the paper is thus to offer such an overview. It identifies and classifies a variety of models available from a social science background (Sections 3 Safety management system (SMS), 4 Safety culture (SC), 5 High reliability organisations (HROs), 6 Accident models and investigations). A historical and ‘genealogical’ approach has been followed and has helped to delineate different ‘research traditions’. The second objective (Sections 7 Combining research traditions, 8 Outlines of a sensitising model) is to present the design rationale of a sensitising model established for industrial safety assessment. The theoretical aspects of this model are then discussed (Section 9).

Section snippets

Four research traditions

The last two or three decades of research by the social sciences in both safety and accident investigation offer many empirical and theoretical insights. Four historical traditions of empirical and theoretical research are distinguished in this paper: safety management system (SMS), safety culture (SC), high-reliability organisations (HROs) and accident investigations and models (AIM).

Introduction to the research tradition

The historical background of the ‘safety management system’ research tradition has been reviewed, for instance, by Hale, 1985, Hale et al., 1991, and more extensively in Hale et al. (1997). It includes empirical and conceptualised knowledge from industrial and consulting practices (e.g. Petersen, 1978), guidance promoted by control authorities (e.g. the Health and Safety Executive – HSE in the UK), standards from international bodies across industries (e.g. the International Standards

Introduction to the research tradition

‘Safety culture’ is very often referred to as a concept introduced by accident investigation reports. For instance, “the term ‘safety culture’ first came to prominence as a result of the International Atomic Energy Agency’s (AIEA) report on the Tchernobyl nuclear accident (…) since then it has been discussed in other major accident enquiries and analyses of safety failures, such as Piper Alpha oil platform explosion in the North Sea and the Clapham Junction rail disaster in London. In both

Introduction to the research tradition

What has been labelled as high reliable organisation (HRO) is an empirical and theoretical research tradition launched by scholars in the mid-eighties. These researchers decided to better understand the specificity of what were seen as technically and organisationally complex high-risk systems considered to perform with a high level of success. Aviation, the army and nuclear organisations were then investigated by a multidisciplinary team representing a mixture of psychological, engineering,

Introduction to the research tradition

The history of investigating organisational dimensions of accidents combined with production of models is several decades old. In the seventies, Turner (1978) was able to analyse more than eighty cases of accident investigation reports in order to elaborate what he called the ‘incubation model’ of disaster. Turner then put forth an empirical and social science mode of research favouring the study of many different cases in search of patterns likely to be shared between them. This strategy has

Different options

In the present situation, one option is to emphasise the specificity and diversity of the research traditions, a strategy followed for instance by Rosness et al. (2004). One therefore selects which tradition is suitable for his/her purpose (e.g. accident investigation). With this option, research traditions are not merged. Instead, they are differentiated to stress what distinguishes them. A different option is to attempt to combine this diversity of traditions into a global model. This second

Design rationale

Fig. 3 reveals the potential for many combinations. For instance, Weick and Sutcliff (2001), but also Hopkins (2005), show how compatible the concepts of ‘safety culture’ (as defined by Reason (1998)), and ‘collective mindfulness’ (as characterised by Weick et al. (1999)) are. They compare these two, then combine them for the purpose of providing design principles for organisations wanting to sustain or reach high levels of safety (an earlier example of comparison is Pidgeon, 1991, Pidgeon, 1998

Discussion

This sensitising model is designed for the purpose of exploring possibilities for improving industrial safety assessment. It is based on a design rationale (i.e. four requirements) that is summarised in relation to the selected models and their combination in Table 2.

This sensitising model is designed as a variation from the practices of technological safety assessment in order to incorporate knowledge from the social sciences. It addresses the theoretical problems identified in the

Conclusion

This paper introduces a sensitising model which aims to provide a perspective to improving safety assessment beyond a technologically oriented approach unable to incorporate the dynamical and systemic side of safety. One core issue is to indicate in foresight what to look at and where to look in attempting to capture patterns that one finds theorised in hindsight by social sciences. For this purpose, the paper specifies a design rationale based on four requirements leading to the selection and

Acknowledgements

The author would like to thank one reviewer for his comments which helped to sharpen the arguments of this paper.

References (121)

  • J.C. Le Coze

    Accident in a French dynamite factory: an example of organisational investigation

    Safety Science

    (2010)
  • J.C. Le Coze

    Towards a constructivist program in safety

    Safety Science

    (2012)
  • N. Leveson

    A new accident model for engineering safer systems

    Safety Science

    (2004)
  • D. Parker et al.

    A Framework for Understanding the Development of Organisational Safety Culture Safety Science

    (2006)
  • J. Rasmussen

    Risk management in a dynamic society: a modelling problem

    Safety Science

    (1997)
  • A. Richter et al.

    Integration, differentiation and ambiguity in safety cultures

    Safety Science

    (2004)
  • S. Sklet

    Safety barriers: definition, classification, and performance

    Journal of Loss Prevention in the Process Industries

    (2006)
  • M. Alvesson

    Understanding Organizational Culture

    (2002)
  • Andler, 2002. Processus cognitifs. In: Andler, A., Fago-largeault, A., Saint-Sernin, B., (Eds.), Philosophie des...
  • Berman, J., Ackroyd, P., 2006. Organisational Drift – A Challenge for Enduring Safety Performance. IChemE Symposium...
  • Bessin, M., Bidart, C., Grossetti, M., 2010. Bifurcations. Les sciences sociales face aux ruptures et à l’événement. La...
  • R.A. Boin et al.

    Assessing NASA’s safety culture: the limits and possibilities of high reliability theory

    Public Administration Review

    (2010)
  • M. Bourrier

    Elements for designing a self-correcting organization: examples from nuclear power plants

  • Bourrier, M., 1999. Le nucléaire à l’épreuve de l’organisation. Presses Universitaires de France. [Nuclear Industry...
  • Bourrier, M., Laroche, H., 2001. «Risque et défaillance. les approches organisationnelles», In: dans, R., Amalberti,...
  • G. Burrell et al.

    Sociological Paradigms and Organizational Analysis: Elements of the Sociology of Corporate Life

    (1979)
  • Chief Counsel Report, 2011. Macondo. The Gulf Oil Disaster. National Commission on the BP Deepwater Horizon Oil Spill...
  • CAIB (Columbia Accident Investigation Board), 2003. Report, vol. 1. Washington...
  • S. Cox et al.

    Safety culture: Philosopher’s stone or man of straw?

    Work & Stress

    (1998)
  • Crozier, M. 1963. Le phénomène bureaucratique....
  • Crozier, M., Friedberg, E. 1977. L’acteur et le système....
  • R.L. Daft et al.

    Toward a model of organizations as interpretation systems

    Academy of Management Review

    (1984)
  • Dalzell, G., Hopkins, A., 2006. Is Hazard Management Working? IChemE Symposium. Series No....
  • Dosse, F., 2010. Le retour de l’évévement. Entre sphinx et phenix. Seuil. [The Return of the Event. Between Sphinx and...
  • W. Evan et al.

    Minding the Machines

    (2002)
  • Farjoun

    History and policy at the space shuttle program

  • S. Gherardi et al.

    What do you mean by safety? Conflicting perspectives on accident causation and safety management in a construction firm

    Journal of Contingencies and Crisis Management

    (1998)
  • A. Giddens

    La constitution de la société

    (1984)
  • A.W. Gouldner

    Patterns of Industrial Bureaucracy

    (1954)
  • Gouldner, A.W., 1959. In: Morton, Robert K., Broom, Leonard, Cottrell, Leonard, Jr. (Eds.), Organizational analysis....
  • Hale, A.R., 1985. The Human Paradox in Technology and Safety. Inaugural Lecture. Safety Science Group,...
  • Hale A.R., 1999. Assessment of safety management systems. Paper to 2nd International Conference on Ergonomics,...
  • A.R. Hale

    Safety management in production

    Human Factors and Ergonomics in Manufacturing

    (2003)
  • Hale, A., 2003b. Note on barriers and delivery systems. In: PRISM Conference,...
  • Hale, A.R., Goossens, L.H.J., Oortman Gerlings, P., 1991. Safety management systems: a model and some applications. In:...
  • Hale, A.R., Gundelmund, F., Goossens, L., 2006. Auditing resilience in risk control and safety management systems. In:...
  • E. Hollnagel

    Barriers and Prevention

    (2004)
  • E. Hollnagel et al.

    Resilience Engineering. Concepts and Precepts

    (2006)
  • Hopkins, A., 2000. Lessons Learnt from Longford. The Esso Gas Plant Explosion....
  • A. Hopkins

    Safety, Culture and Risk

    (2005)
  • Cited by (0)

    View full text