Elsevier

Safety Science

Volume 48, Issue 10, December 2010, Pages 1402-1411
Safety Science

Organisational safety indicators: Some conceptual considerations and a supplementary qualitative approach

https://doi.org/10.1016/j.ssci.2010.05.016Get rights and content

Abstract

This article discusses the extent to which indicators can represent organisational qualities in relation to safety and how a qualitative approach called the Operational Safety Condition (OSC) method can be a supplement and help improve safety. In light of the recent Safety Science debate on safety indicators, we suggest that it is difficult to capture organisational conditions using indicators, although they are indisputably important when identifying the risk of accidents. Safety climate and risk analysis approaches are discussed as methods that can build and assess indicators in relation to organisational safety quality. OSC and similar qualitative approaches can capture the complexity of organisational conditions, aid organisational learning at a double loop level and offer a tool for risk management.

Introduction

In industry and business, quantitative indicators are used to monitor performance in areas such as finance, efficiency, customer satisfaction and safety. Well-known indicators are the ubiquitous key performance indicators (KPIs), which are used for different strategic purposes. In the safety research community, indicators have been extensively debated, as manifested in a special issue of Safety Science. Hopkins (2009) initiated a discussion on a variety of themes including how the terms “leading” and “lagging“ should be understood, the different kinds of indicators and the effects of using them.

This article has a twofold objective. First, we wish to explore safety indicators when they address organisational qualities. We will argue that the typical format of indicators has some limitations when they are indications of organisational safety levels, particularly when it comes to more complex causal chains and systemic failures. Second, we will present how broader qualitative approaches can supplement indicators and support efforts to increase safety levels, exampled by the Operational Safety Condition (OSC) method. This is an organisational safety verification and improvement method that has recently been developed for use in the oil and gas industry.

Organisational factors are regarded as important root causes of accidents, potentially producing unsafe acts and influencing local workplace factors. In particular, the organisational element is important in large-scale accidents, where technical failures or simple human error cannot solely serve as explanations, since their occurrence might require the malfunction of several barriers (Reason, 1997).

The importance of organisational conditions in relation to major industrial accidents has been highlighted in several major accident investigations during the past 30 years. One example is the investigation after the British Petroleum refinery catastrophe in Texas City in March 2005 (Baker, 2007) that focused extensively on several organisational deficiencies, such as safety culture, safety management systems, performance evaluation, corrective action and corporate oversight. In addition, general human error frameworks that could be used in accident investigations have been developed (e.g. Shappell and Wiegmann, 2000).

Even though investigations provide important and valuable insights into important organisational conditions and how they contribute to major accidents, much work has been invested in trying to establish proactive indicators of organisational safety performance. Harms-Ringdal (2009: p. 481) describes safety indicators as observable measures that provide insight into a concept – safety – that is difficult to measure directly”. Proactive or leading indicators have been subject to much debate, as illustrated in the elaborate discussion on the lead/lag distinction regarding indicators in Safety Science. For example, Dyreborg (2009) defines leading indicators as proactive measures of performance before any unwanted outcomes have taken place. Lagging indicators are, by contrast, representations of unwanted outcomes or some measure of the harm themselves. Thus, lagging indicators could be used to evaluate the quality of leading indicators, because there should be an association between the two. A good lead indicator should have a causal link to negative safety outcomes (Grote, 2009).

Our research has focused mainly on the organisational aspects of safety (e.g. Almklov and Antonsen, 2010, Kongsvik and Bye, 2004, Antonsen et al., 2007, Kongsvik and Fenstad, 2007). We have looked at how a multitude of organisational aspects can combine to influence safety, for example, management, personal networks, procedures, reporting systems, safety culture, informal and formal communication, shift systems and outsourcing. Typically, such factors are discussed as underlying causes of accidents and events. Leading or proactive indicators are often designed to address such issues.

In the following, we will first present and discuss two different approaches to organisational safety indicators. We will claim that it is difficult to establish good indicators for organisational safety, partly because of the multiple layers of intervening variables between organisational conditions and accidents, and the complexity and dynamic nature of organisational safety itself. Then we will present the OSC approach as a possible supplement to quantitative indicators on organisational safety. We will claim that such approaches offer the opportunity for “double loop” learning as well as tailoring quantitative, local safety indicators.

Section snippets

Organisational safety indicators

The two research traditions that will be presented are (1) the safety climate tradition and (2) the risk analyses tradition. These have in different ways attempted to construct valid organisational safety indicators. We will provide examples of the kinds of organisational factors proposed by these two traditions and how these dimensions/factors are measured. We will also look at how they relate to safety performance and to what extent they can be validated as safety performance indicators.

A qualitative supplement to indicators: OSC

One author has participated in the development of OSC, which is a proactive organisational safety verification and improvement method that aims to reduce the risk of major accidents (Sklet et al., 2010). The focus here is on process/hydrocarbon (HC) leaks, because such leaks are a major contributor to the risk of major accidents. The main output of this method is qualitative descriptions of organisational risk controlling systems as well as some quantitative measures. An important contribution

Organisational safety indicators

The quest for good safety indicators has been long. Despite huge efforts developing them and appurtenant data gathering, they are is still subject to much discussion, as the Safety Science debate illustrates.

In the safety climate tradition, indicators or factors have been produced, which have some prospective correlation with safety performance. Still, the found correlations tend to be moderate or weak, and many studies show no such correlations at all. One way of explaining these results is

Conclusion

We have illustrated that organisational safety indicators, from the safety climate and risk analyses traditions, have some limitations. There is a huge variation in the organisational factors used and the indicators developed to measure them. It has also been challenging to establish a robust link between organisational safety indicators and safety performance. In addition, the use of organisational safety indicators demands thorough consideration to ensure that the most important safety issues

Acknowledgements

The authors wish to sincerely thank Statoil and the OSC team that participated in developing the OSC method: Stein Haugen, Arne Jarl Ringstad, Jorunn Seljelid, Snorre Sklet, Sunniva Anette Steen, Lars Tronstad, Jan Erik Vinnem and Irene Wærø. We also wish to thank Professor Karina Aase and researcher Stian Antonsen for constructive comments on an earlier version of the article.

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