The use of precursor data has many advantages. First, in industries where severe accidents are sparse (such as nuclear power), precursor data can be a valuable information source on accident characteristics and frequencies, either directly or as a supplement to risk analysis. Therefore, it is worthwhile to make full use of precursor data as an indicator of plant performance; e.g., in estimating severe accident frequencies, or in prioritizing risk management activities. Moreover, precursor data inherently incorporated the effects of factors such as human errors and inter-system dependencies.

However, care must be taken in the interpretation of accident precursors. For example, precursor data are often subject to widely divergent interpretations, since accident precursors are neither successes nor failures, but rather partial failures. Similarly, a precursor at one facility may be only partially relevant to other facilities. Finally, there is no consensus on the best approach for organizations to use in collecting and responding to accident precursor data. The design of reporting systems that simultaneously foster accurate reporting, individual accountability for errors, effective root cause analysis, and maximal use of precursor data is therefore a challenging task.

The purpose of the workshop is to bring together researchers and practitioners working on the analysis of accident precursor data form a variety of disciplines (e.g., risk analysis, statistics, engineering, ergonomics, psychology, sociology, organizational behavior) and a variety of industries (e.g., nuclear power, aerospace, aviation, chemical processing, telecommunications, and defense).

The aims of the workshop are: (1) where possible, to reach consensus on effective methods for the analysis and use of accident precursor data; and (2) on issues where consensus cannot yet be reached, to identify outstanding research topics and recommend needed directions for further research.

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