Measuring Safety Performance: Strategic Risk Data (Airline Safety and Human Factors Issues)

摘要

Airlines measure safety performance to understand the state of the operations. Much data is collected but it is far from obvious how to handle all the data, act on the result or even to know what can be measured in a meaningful way. The overall purpose of this study is to propose a method for airlines regarding how to evaluate and improve their current practices related to safety performance monitoring and measurement. Mandatory and voluntary reporting systems capture aspects of the operations but are largely retrospective and do not by themselves provide a predictive safety performance monitoring capability. Flight data monitoring programs and other data sources can add a predictive capability. It is of great importance to understand what data to look for and to understand the relationships between various pieces of data to be able to improve in the name of safety. There is also a great need for practical guidance on how to develop a more predictive safety management. Human factors is the field believed to have most potential to substantially improve safety. In recent research an approach to airline safety management describes the organizational processes in layers of real-time operational cycles, real-time operations support, tactical and strategic organizational processes. When a systemic view on human factors, including individual, technical and organizational aspects, is applied to this organizational structure it forms a matrix for strategic risk data that may be used in development of a comprehensive safety parameter scope. It is believed that the currently dominant safety model approach with the discussion of causality and of latent conditions as root cause or causes still has potential to improve safety due to the existing gap between theory and practice. It is, however, a great challenge to bridge this gap. In this research a five-step methodology is proposed to systematically review: 1) currently known safety performance indicators directly related to safety, 2) contributory factors identified in reports, 3) other contributory factors with validated relationship to safety and 4) links between on the one hand the selected safety performance indicators and identified contributory factors and on the other hand contributory factors linked to other validated sources such as human factors theory. With this revision at hand and 5) using all available data sources it will be more feasible to justify current safety activities and the relevance of data collected. This method is also believed to identify feasible areas of improvements and contribute to balancing resource requirements in relation to the safety benefits coming out of the safety program.