Knowledge risk management: a framework

TL;DR: The paper examines how conventional approaches to risk management based on decision tree methods are ineffective, and proposes and tests an alternative KRM model, which improves the accuracy of risk assessment by reducing subjectivity caused by cognitive bias.

Abstract: Purpose – There has been increased interest in application of knowledge management (KM) in managerial issues as a way of demonstrating the field’s value. There has also been an increasing focus on risk management (RM) in response to growing organisational awareness of corporate and social responsibilities. This paper seeks to contribute to the emergence of a new field of research – referred to as knowledge risk management (KRM), which applies KM tools and techniques to the management of organisational risk. Design/methodology/approach – The approach takes the form of building on an empirical study of the Australian Department of Defence using case study methods. Findings – The paper examines how conventional approaches to risk management based on decision tree methods are ineffective, and proposes and tests an alternative KRM model. Research limitations/implications – A limitation is that the paper is based on a single case study. Originality/value – The model provides managers with a way to differentiate amongst risks and prioritise for action. Its main value is to reduce the cognitive bias inherent in traditional decision methods for risk assessment. The KRM model improves the accuracy of risk assessment by reducing subjectivity caused by cognitive bias.