Managing the Human Factor in the Incident Investigation Process

Managing the Human Factor in the Incident Investigation Process

Burggraaf, J.
Groeneweg, J.

2016

Incident investigation and analysis are crucially important parts of the learning from incidents process. They are also highly complex tasks, especially analyzing information to relate "effects" to "causes." It requires the processing and judgment of vast amounts of information under often demanding circumstances like time pressure and lack of resources. These task elements are typical ingredients for the presence of so-called cognitive biases. These biases can have a negative influence on the validity of an investigation and can lead to incorrect and hence ineffective recommendations. This is also a serious issue from a legal perspective as in many cases an investigation has to be able to withstand scrutiny in legal proceedings. For individual investigators and teams it is very difficult to identify these biases by themselves if they do not know what "red flags" to look for. The questions posed in this paper are: What kind of cognitive biases are present in incident analyses and what can be done to detect and prevent them? Nine incident analysis reports have been evaluated to identify cognitive biases. These reports were written by certified investigators of an internationally operating safety consultancy. We extracted the factual elements from these reports, re-analyzed the incidents, and compared the conclusions to the original results. We identified cognitive biases in all reports. The investigators can detect these biases themselves at an early stage of an investigation. Once identified, the investigators can update the analysis or search for extra information in supplemental investigations. The avoidance of cognitive biases can help organizations to avoid implementing ineffective recommendations and, maybe even more important, make sure that effective improvements are not missed.

Ergonomics
Upstream Oil & Gas
Information
Effortful thought
Neural network
Incident analysis
Incident investigator
Recommendation
Outcome bias
Artificial Intelligence
Work and Employment
Healthy Living

http://resolver.tudelft.nl/uuid:b7df0208-2f05-4e97-bb48-054d42f42df0

https://doi.org/10.2118/179207-ms

971210

9781613994436

SPE International Conference and Exhibition on Health, Safety, Security, Environment, and Social Responsibility, April 11–13, 2016, Stavanger, Norway

conference paper