Individual latent error detection: is there a time and a place for the recall of past errors?

Latent error detection: A golden two hours for detection

Undetected error in safety critical contexts generates a latent condition that can contribute to a future safety failure. The detection of latent errors post-task completion is observed in naval air engineers using a diary to record work-related latent error detection (LED) events. A systems view is combined with multi-process theories to explore sociotechnical factors associated with LED. Perception of cues in different environments facilitates successful LED, for which the deliberate review of past tasks within two hours of the error occurring and whilst remaining in the same or similar sociotechnical environment to that which the error occurred appears most effective. Identified ergonomic interventions offer potential mitigation for latent errors; particularly in simple everyday habitual tasks. It is thought safety critical organisations should look to engineer further resilience through the application of LED techniques that engage with system cues across the entire sociotechnical environment, rather than relying on consistent human performance.

Human Factors in Financial Trading: An Analysis of Trading Incidents

OBJECTIVE

This study tests the reliability of a system (FINANS) to collect and analyze incident reports in the financial trading domain and is guided by a human factors taxonomy used to describe error in the trading domain.

BACKGROUND

Research indicates the utility of applying human factors theory to understand error in finance, yet empirical research is lacking. We report on the development of the first system for capturing and analyzing human factors-related issues in operational trading incidents.

METHOD

In the first study, 20 incidents are analyzed by an expert user group against a referent standard to establish the reliability of FINANS. In the second study, 750 incidents are analyzed using distribution, mean, pathway, and associative analysis to describe the data.

RESULTS

Kappa scores indicate that categories within FINANS can be reliably used to identify and extract data on human factors-related problems underlying trading incidents. Approximately 1% of trades (n = 750) lead to an incident. Slip/lapse (61%), situation awareness (51%), and teamwork (40%) were found to be the most common problems underlying incidents. For the most serious incidents, problems in situation awareness and teamwork were most common.

CONCLUSION

We show that (a) experts in the trading domain can reliably and accurately code human factors in incidents, (b) 1% of trades incur error, and (c) poor teamwork skills and situation awareness underpin the most critical incidents.

APPLICATION

This research provides data crucial for ameliorating risk within financial trading organizations, with implications for regulation and policy.