Accidents: A discrepancy between indicators and facts!

Körvers, P.M.W.; Sonnemans, Pjm Peter

doi:10.1016/j.ssci.2007.06.004

Cited by 40 publications

(15 citation statements)

References 12 publications

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“…For the latter part of the answer we refer to Körvers (2004) and Körvers et al (2006), where it is shown that commonly used safety performance indicators (SPI's) do not cover ineffective control loops, nor do they 'detect' the kind of precursors identified in the FACTS database, i.e. the 'normal' operational disruptions that occur daily.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Accidents in the chemical industry: are they foreseeable?

Sonnemans

Körvers

2006

Journal of Loss Prevention in the Process Industries

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Section: Resultsmentioning

confidence: 99%

“…Körvers et al (2006) show that the common safety performance indicators currently in use, do not cover all risky precursors. A specific category is not included, namely those disruptions that recur frequently and are not seen as directly linked to an unsafe situation, as was also mentioned in the previous section.…”

Section: Preventionmentioning

confidence: 98%

Accidents in the chemical industry: are they foreseeable?

Sonnemans

Körvers

2006

Journal of Loss Prevention in the Process Industries

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“…This has led to conclusions like: organizations need to be clear on what they want reported and give guidance to employees (Hopkins 2009). In keeping with this focus, Körvers and Sonnemans (2008) developed a list of warning signals from their analyses of 70 accidents. Research has also addressed the factors that support or hinder reporting.…”

Section: Collective Knowledge In Organizationsmentioning

confidence: 99%

Preventing black swans: incident reporting systems as collective knowledge management

Maslen

Hayes

2015

Journal of Risk Research

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In hazardous industries, disasters are mercifully rare and yet the potential is ever present. For this reason, companies and industries as a whole put substantial effort into gathering information about past small failures and their causes in an attempt to learn how to prevent more serious events. Despite these efforts, recent research has captured how organizations can 'fail' to learn. Disastrous events can become 'black swans' and remain unpredicted despite the existence of information warning of them. This article engages with this challenge by analyzing incident-reporting systems as a tool for collective knowledge. Drawing together the literatures on organizational knowledge management and incident reporting, we examine incident-reporting systems as used and as structured. We explore the potential use of incident-reporting systems for mediation and synchronization of knowledge within and across groups of professionals and organizations. We also address the social practices that translate information in databases into collective knowledge. Building on the work of Hecker, we argue that research concerned with incident reporting and organizational learning would benefit from using 'knowledge' and specifically 'collective knowledge' as its reference point. We show that conceptualizing this problem in terms of 'reporting' and 'learning' distracts attention from the knowledge needs for people to learn. We argue that we must ask: What do people need to know to play their part in major accident prevention? And how is that knowledge effectively shared? We conclude with an empirical research agenda in light of this investigation.

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“…Hazardous conditions lack the 'unplanned event', but present an undesirable condition that could potentially lead to the close call, injury, illness, fatality, damage, or spill. Close call (near miss) reporting was initially developed to study low frequency events with significant potential consequences in civil aviation, nuclear power plants, and chemical plants (van der Shaaf and Kanse 2004, Körvers andSonnemans 2008, van der Schaaf 1995).…”

Section: Introduction To Close Call (Near Miss) Reportingmentioning

confidence: 99%

Reporting Practices for Close Call (Near Miss) Reporting Systems

Craig

Papillon

Curry

et al. 2014

Day 1 Mon, May 05, 2014

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This paper identifies best practices for reporting close calls (near misses) in the maritime industry. The practices were identified by reviewing approximately 44,000 actual close call reports from 27 data sources. Even though the close call data is provided in a wide variety of formats, the data demonstrates a surprising degree of uniformity in the collection of the close call data and resolution of the close calls with most organizations capturing an incident description and incident resolution. A number of organizations also have formal corporate response feedback mechanism for all incidents. The analysis demonstrates that many features of close call reporting systems discussed in the literature are being implemented in practice including avoiding blame, disseminating close callreports, and developing effective corrective measures. Based on the review of industry practices and industry feedback, a sample close call reporting form and taxonomy for close calls will be developed. 2OTC-25078-MS 2. ChallengesOne of the primary challenges of establishing a cross-industry injury and close call database results from differences in the injury/close call information that is collected and the multiple formats used by different organizations. This is particularly true with close call records. DatabaseCurrently, industry partners have access to the injury database, the close call database and a Mariner Safety Document Center that contains numerous examples of toolbox talks, ergonomic discussion papers, and safety spotlights, etc. All materials developed for the Mariner Safety Document Center are based on the data contained in the Mariner Personal Safety Database. Database revisions and improvements are based on user (industry partner) feedback. Examples of revisions and improvements include the use of stemming and synonyms (similar to a web search engine), cause, type, and location based drop down menus, and searches by vessel type. 4. Injury DataThus far, nine different industry partners have provided injury data, representing approximately 15,000 reports. Though the data varies, commonly re-occurring data fields include injury type, potential, root or cause for the incident, equipment involved, location on the vessel, vessel type, task(s) at the time of event, and demographic characteristics of the crewmembers involved. From this data, injury causes, types, locations, and their corrective actions and lessons learned have been shared with the industry partners. 5. Close Call (Near Miss) DataThus far 27 different data sources have provided close call data, representing approximately 44,000 reports. As with the injury data, the close call data reported varies amongst data sources. For close calls, commonly reoccurring data fields include close call type, potential, root or cause for the incident, equipment involved, location on the vessel, vessel type, task(s) at the time of event, and demographic characteristics of the crewmembers involved. From this data, close call causes, types, locations, and their corrective actions a...

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Accidents: A discrepancy between indicators and facts!

Cited by 40 publications

References 12 publications

Accidents in the chemical industry: are they foreseeable?

Accidents in the chemical industry: are they foreseeable?

Preventing black swans: incident reporting systems as collective knowledge management

Reporting Practices for Close Call (Near Miss) Reporting Systems

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