Abstract
Causal-tree methods such as root cause analysis (RCA) are the oldest and the most widespread methods used to analyze the causes of adverse events. They are often seen as essential prerequisites to risk control. Over the last few years, however, a number of limitations of RCA have been pointed out. Starting from the limitations currently identified and from our own occupational health and safety specialists’ experience, we have developed a new perspective for the analysis of accident causes, called constructive cause analysis (CCA). CCA is part of a tradition of activity-focused ergonomics. It posits that safety is mostly based upon the skills of individuals, at both operational and organizational levels, and it also leads to identifying positive elements in the analyzed situation. In line with the historico-cultural theory of activity, CCA serves the dual objectives of knowledge and action: the modifications found in CCA are based upon the confrontation of knowledge. The purpose of this article is to describe CCA. A case study from our own interventions illustrates the method.

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The main argument against this implementation of the method is that it is time consuming. This approach involves several people working for several hours. Our answer is based upon the literature findings. Studies have shown that the in-depth analysis of the causes of one or several events is more effective than the statistical processing of the set of identified risks (Amalberti 2001; Leclercq et al. 2013; Vincent 2004). In other words, it would appear to be more effective for several people to analyze one case fully than to have one person analyze several cases.
The techniques mentioned are more about the analysis of the activity because it is more difficult to verbalize the activity than the task. It is, of course, also necessary to understand the task and the dialectical relation that exists between task and activity. Hence, these interviews must be supplemented by semi-structured interviews and document analysis to understand the task and the rationale behind the design of the work.
This statement does not mean that all judgements, interpretations, and opinions should be removed from safety analyses. It only means that this type of information should be excluded at this stage of CCA. In parallel with CCA, the so-called naive causal explanations (i.e., those spontaneously provided by operators or the persons directly exposed to risks and accidents) constitute valuable information likely to throw light upon events and supplement the method. Before the CCA, they represent clues and leads for the data collection. Afterward, they open avenues to continue the intervention, extend it, or else think of new methods (Kouabenan 2009).
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Acknowledgements
This article would never have seen the light of day without the inquisitive, candid, or challenging discussions held with the CNAM audiences and Paris 8 students. I am especially grateful to Anne Bationo-Tillon and Jacques Leplat who have the knack of opening new avenues for thought with a couple of words in a corridor.
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Cuvelier, L., Bencheckroun, H. & Morel, G. New vistas on causal-tree methods: from root cause analysis (RCA) to constructive cause analysis (CCA). Cogn Tech Work 19, 13–30 (2017). https://doi.org/10.1007/s10111-017-0404-8
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DOI: https://doi.org/10.1007/s10111-017-0404-8