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The objective of this study was to propose improvements in an algorithm for classifying error types of front-line workers. The improvements involved: (a) making recommendations on organizing the data needed to apply the algorithm (e.g. identify actions and decisions that may serve as a reference for analysing the types of errors) and (b) drawing up guidelines for interpreting the questions that are part of the algorithm (e.g. how to define what counts as a procedure). The improvements were identified on the basis of testing the algorithm on construction sites, an environment in which it had not yet been implemented. Thus, 19 occupational accidents which had occurred in a small-sized construction company were investigated and the error types of both workers who had been injured and crew members were classified. The accidents investigated were used as a basis both to illustrate how the improvements proposed should be put in practice and to illustrate how practical insights for safety management might be derived from the algorithm.

This article introduces a method for assessing health and safety management systems (MAHS) that has two innovative characteristics: (a) it brings together the three main auditing approaches to health and safety (HS) – the structural approach (which assesses the system prescribed), the operational approach (which assesses what is really happening on the shop-floor) and the performance approach (which assesses the results of performance indicators); (b) it emphasizes the resilience engineering perspective on HS, which takes into consideration four major principles (flexibility, learning, awareness, and top management commitment). Such principles underlie seven major assessment criteria, which in turn are divided into items (e.g. hazard identification from a resilience perspective is an item that belongs to the criteria of production processes). The items are sub-divided into statements, which are the requirements that should be assessed based on interviews, analysis of documents and direct observations. Within the 112 requirements proposed, 38 of them have clear links with at least one out of the four resilience engineering principles adopted. The remaining requirements are based on traditional assumptions underlying the so-called best practices of HS management. The results of the assessment for each item are expressed by a score on a scale of compliance with the established requirements, ranging from 0% to 100%. The specific score within that scale is obtained from tables used to assess applications for the Brazilian national quality award. The MAHS was tested in a case study that was carried out in a factory that manufactures automobile exhaust systems, located in Brazil.