Organisational knowledge in high-risk industries: supplementing model-based learning approaches

Abstract

High-risk industries are often facing a dilemma in their approach to creating a more competent and safe industry: they are excluded from some of the most effective learning processes such as trial-and-error learning and learning from failures and errors, due to the potentially catastrophic outcome associated with mistakes. As a consequence, these industries commonly rely on formal models of information gathering and dissemination. In a learning perspective, such approaches have often shown to be ineffective and unreliable, disregarding the social and contextual aspects of organisational knowledge. In a safety perspective, these formal repositories of experience and knowledge are often highly necessary and strictly enforced due to the high-risk environment. Is this a dilemma without solution? Are there alternative learning approaches to collectively develop, make sense of, and disseminate tacit and sticky knowledge in high-risk industries? Examples from studies of different high-risk industries are used to highlight these questions.