October 30, 2024Dom Cooper analyses assumptions in common safety management methods.
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Numerous claims (i.e., assertions) and counterclaims exist about the efficacy of various safety improvement approaches. For example, a claim that monitoring accident and injury statistics provides feedback about safety performance, compared to a counterclaim that accident statistics don’t predict safety performance. Questioning can sometimes lead to heated public debate and tribalism within OSH, rather than moving the discipline forward.
Equally, assumptions related to OSH constructs and methods are abound within the safety profession. Assumptions are “beliefs or feelings that something is true or will happen, even though there is no proof”; in essence, assumptions are tentative speculations until confirmed via feedback[i].
It follows that if our beliefs are wrong, our assumptions must also be mistaken. Erroneous assumptions can arise from taking a known fact but coming to the wrong conclusion[ii], uncritically projecting our knowledge onto others, or our prior contextual beliefs[iii]. One example of an erroneous assumption is that poor mental health directly causes accidents (robust empirical support is lacking). Conversely, evidence suggests that good safety performance can enhance mental health and wellbeing, highlighting the complex relationship between these factors.
Clashes between different assumptions and claims of efficacy are common in the OSH profession; attempts to resolve them typically mean considering other viewpoints and presenting reasoned arguments to support or refute them.
Recently, I had cause to use a structure dividing ‘claims’ into types (i.e., a typology of claims[iv]) for evaluating rhetorical arguments (i.e., persuasions that a belief, opinion, or course of action is true). The typology speaks to claims made about: classification (i.e., facts), definitions (i.e., understanding of facts), cause & effect (i.e., one thing leads to or causes another), value (i.e., judgments of worth), and solutions (i.e., resolving issues).
“Misalignment between assumptions and claim types can lead to misunderstandings and create difficulties”
The strongest claims speak to evidence (i.e., facts and cause & effect), as they can usually be verified. Claims of definition often involve disputes over the classification of facts and their meaning, claims of value usually involve subjective judgments about the worth, morality, or quality of something, and claims of solutions usually speak to strategies, policies, and methods to change the status quo.
Finding multiple claim types is common within propositions about a product, service, or way of doing things. When these and the underlying assumptions are aligned, the case being made is more likely to be coherent and valid. However, misalignment between assumptions and claim types can lead to misunderstandings and create difficulties. Therefore, understanding the relationship between the two is crucial, both for constructing strong arguments and for critically analysing others’. As such, trying to demonstrate the practicality of the claim typology, I thought it useful to explore the assumptions and claims regarding safety management methods commonly used to help reduce the number of accidents.
Risk assessments
Risk assessments are subjective by nature, and many assumptions underpin them. For example, we assume that those doing risk assessments have the background knowledge to know what they are doing, that they are identifying all risks associated with a task, and that the frequency, likelihood, and severity of occurrence used to prioritise risk controls using matrices are reliable and accurate[v]. Despite validity concerns about quantitative risk assessments (QRA), evidence shows such assessments have led to incident reductions[vi], supporting cause & effect and value (injury prevention) claims. Categorising risks identified, assessed, and controlled would support a claim of facts (the hazard(s)), definitions (understanding the threat(s) posed), and solutions (risk controls).
Procedural compliance
There are many competing assumptions about procedures; for example, they either enable people and facilitate best practices or are bureaucratic and coercive. Non-compliance with procedures has led to many actual and potential catastrophes. Research shows safety performance improves when procedures are systematically developed to match tasks[vii].
Thus, claims of facts (how a task is done, with which resources and known constraints), definition (understanding of the task sequencing of activities to keep people safe), cause & effect (compliance leads to reliable and repeatable success), value (people are kept safe), and solutions (the procedure is correct and understandable) would be valid.
Safety training (Competence)
Assumptions about safety training are often based on accidents caused by a lack of knowledge and/or competence[viii] (although other factors may also be in play). Reviews show safety training positively influences safety behaviour[ix] and incident reduction, particularly when combined with other initiatives[x]. Thus, claims of fact (topic content), definition (understanding of the topic), cause & effect (competence training reduces injuries), value (effective incident prevention method), and solutions (training can bridge identified knowledge gaps) would apply.
Accident investigations
Most incident investigations assume that adverse effects occur from a direct cause, resulting in the search for root causes. Contrary assumptions state safety systems are too complex (usually without defining complexity) to determine a root cause, and the focus should be on the why rather than the what or how.
Evidence[xi] shows thorough incident investigations reduce similar future incidents by changing the causal circumstances and conditions, supporting claims of fact and cause & effect. Definition claims (understanding of how an adverse event unfolded), value claims (preventing repeat incidents), and solution claims (implementing corrective actions) would also be valid.
Lessons learned
Assumptions about a lessons-learned process include organisations that fail to learn from incidents[xii], versus those that are fundamentally about changing the status quo via corrective or preventive actions[xiii]. The former can stem from a lack of investigation, a failure to record and retain information, key personnel changes, or a mix of all three.
Regarding the latter, changing the status quo is evidenced in studies of operations[xiv] and patient safety[xv], leading to valid claims of fact (root causes), definition (understanding of the issues), cause & effect (if A then B), value (prevention of a repeat incident), and solutions (problem resolution).
Safety leadership
It is generally assumed that ineffective safety leadership is detrimental to good safety; for example, prioritising production over safety, ignoring employees’ safety concerns, creating a culture of fear, etc. Conversely, it is assumed that effective safety leadership positively improves and influences safety culture and performance, with evidence showing servant leadership has a bigger impact on injury reduction than transformational and transactional leadership[xvi].
Such evidence supports claims of fact (leadership style is important), definition (understanding of safety leadership), cause & effect (leadership directly impacts safety behaviour), value (leadership influences safety culture), and solutions (leadership training).
Safety communications
Assumptions underpinning safety communications speak to the transfer of critical safety information to influence people’s safety behaviour. Multiple communication methods (toolbox talks, incident reports, safety alerts, rules & procedures, etc.) exist to convey information, making it a critical aspect of safety management. We know, for example, that poor safety communications are involved in many fatalities in construction[xvii].
Logically, where there are good safety communications (e.g. providing feedback), injuries should reduce, which they do[xviii]. Again, valid claims of facts (critical safety information) cause & effect (reduces injuries), value (provides relevant information), and solutions (two-way safety communications ensure dialogue and understanding) can be made.
Safety culture
Assumptions about a culture of safety include ‘there’s no such thing’ versus ‘it’s a useful construct linked to many incident types’. One organisational [safety] culture model is predicated on invisible, unknown, core ‘taken-for-granted’ assumptions; safety success equates to identifying and changing these (and hoping that leads to different actions and artefacts). Evidence shows such assumptions don’t play a significant role, whereas explicit safety culture attributes do (e.g., profits before safety, a culture of fear), as they are empirically linked to many safety incident metrics[xix].
Moreover, specific interventions to improve a culture of safety have been shown to reduce incidents[xx], supporting valid claims of cause & effect (injury reduction), value (cultural improvement), and solutions (means and methods).
This necessarily brief tour of safety methods shows each claim type provides a useful framework for evaluating the pros and cons of assumptions and debates about the most effective means to reduce injuries. Particularly useful to those studying OSH, each provides a different lens and helps to identify single or multiple claims embedded within any particular argument or proposition. The analyses above may or may not be entirely accurate (I am not claiming they are definitive), but each analysis presented lends itself to focused and reasoned debate.
The framework is offered in the hope that common usage helps to lessen heated debate and tribalism within the OSH profession, so that together we can all concentrate on reducing serious injuries & fatalities and debilitating physical ill-health cases. As the saying goes “to use it, is to make it useful”.
References
[i] Krauss, R. M. & Fussell, S. R. (1991b). Perspective-taking in communication: Representations of others’ knowledge in reference. Social Cognition, 9, 2-24.
[ii] Fussell, S. R. & Krauss, R. M. (1989a). The effects of intended audience on message production and comprehension: Reference in a common ground framework. Journal of Experimental Social Psychology, 25, 203-219.
[iii] Nickerson, R. S. (1999). How we know—and sometimes misjudge—what others know: Imputing one’s own knowledge to others. Psychological Bulletin, 125(6), 737.
[iv] Fahnestock, J. & Secor, M. (1988). The stases in scientific and literary argument. Written Communication, 5(4), 427-443.
[v] Flage, R. & Askeland, T. (2020). Assumptions in quantitative risk assessments: When explicit and when tacit?. Reliability Engineering & System Safety, 197, 106799.
[vi] Gamboa-Sánchez, M. C., Cotrina-Teatino, M. A., Vega-Gonzalez, J. A., Noriega-Vidal, E. M., Arango-Retamozo, S. M., & Marquina-Araujo, J. J. (2024). Effective critical risk management in welding operations for mining: A case study on incident reduction. International Journal of Safety & Security Engineering, 14(4).
[vii] Wachter, J. K. & Yorio, P. L. (2014). A system of safety management practices and worker engagement for reducing and preventing accidents: An empirical and theoretical investigation. Accident Analysis & Prevention, 68, 117-130.
[viii] Gerarda Power, N. & Baqee, S. (2010). Constructing a ‘culture of safety’: An examination of the assumptions embedded in occupational safety and health curricula delivered to high school students and fish harvesters in Newfoundland and Labrador, Canada. Policy and Practice in Health and Safety, 8(1), 5-23.
[ix] Robson, L. S., Stephenson, C. M., Schulte, P. A., Amick III, B. C., Irvin, E. L., Eggerth, D. E., Chan, S., Bielecky, A.R., Wang, A.M., Heidotting, T.L., Peters, R.H., Clarke, J.A., Cullen, K., Rotunda, C.J., & Grubb, P. L. (2012). A systematic review of the effectiveness of occupational health and safety training. Scandinavian Journal of Work, Environment & Health, 193-208.
[x] Li, J., Pang, M., Smith, J., Pawliuk, C., & Pike, I. (2020). In search of concrete outcomes—a systematic review on the effectiveness of educational interventions on reducing acute occupational injuries. International Journal of Environmental esearch and Public Health, 17(18), 6874.
[xi] Kletz, T. (2007). Learning from Accidents. Routledge.
[xii] Drupsteen, L., Groeneweg, J., & Zwetsloot, G. I. (2013). Critical steps in learning from incidents: Using learning potential in the process from reporting an incident to accident prevention. International Journal of Occupational Safety and Ergonomics, 19(1), 63-77.
[xiii] Argyris, C. & Schon, D. (1978) Organisational Learning: A Theory of Action Perspective. Reading, Mass: Addison Wesley.
[xiv] Prevette, S. S. & Bilson, H. E. (2008, February). Integrating Safety and Lessons-Learned Data with Human Performance for Successful Management and Oversight–8053. In 2008 Waste Management Symposium.
[xv] Zeng, J., Nyflot, M. J., Jordan, L. E., Sponseller, P. A., Novak, A., Carlson, J., Ermoian, R. P., Kane, G. M., & Ford, E. C. (2016). Best practices for safety improvement through high-volume institutional incident learning: Lessons learned from 2 years. Journal of Radiation Oncology, 5, 323-333.
[xvi] Cooper, M. D. (2015). Effective safety leadership: Understanding types & styles that improve safety performance. Professional Safety, 60(02), 49-53.
[xvii] Whittington, C., Livingston, A., & Lucas, D. A. (1992). Research into Management, Organisational and Human Factors in the Construction ndustry. Sudbury, Suffolk: HSE Books.
[xviii] Saari, J. (1990). On strategies and methods in company safety work: From informational to motivational strategies. Journal of Occupational Accidents, 12(1-3), 107-117.
[xix] Cooper, M. D., Collins, M., Bernard, R., Schwann, S., & Knox, R. J. (2019). Criterion-related validity of the cultural web when assessing safety culture. Safety Science, 111, 49-66.
[xx] Aburumman, M., Newnam, S., & Fildes, B. (2019). Evaluating the effectiveness of workplace interventions in improving safety culture: A systematic review. Safety Science, 115, 376-392.
Excellent paper!!!
Just wanted to say your SHP article on claims typology is brilliant – it’s a proper analytical framework that really works. I’ve been testing it extensively, especially when paired with AI for systematic analysis.
Adding legal requirements and moral considerations makes it even more robust for real-world safety applications. It’s particularly good at exposing vague safety theories that lack substance whilst validating approaches with genuine merit.
As you said – “to use it, is to make it useful” – and it’s proving incredibly useful for cutting through safety rhetoric to find what actually works.
Excellent work Dom, few will understand or appreciate the usefulness of this tool.