An enhanced data-analytic framework for integrating risk management and performance management

Abstract There is increasing interest for agencies and industries to develop risk management processes for a wide variety of applications. Traditional risk management processes are motivated by controlling risk and avoiding losses. In contrast, other organizational processes focus on managing performance and value generation. In this paper we argue that risk management also adds an important contribution to these processes. However, this requires “proper” risk management extending beyond narrow safety oriented perspectives built on quantitative risk analysis and tolerability/acceptance criteria. There is need for a broad risk-performance framework with uncertainty being a main component of risk, and where knowledge and surprises are adequately reflected. In the paper we present and discuss such a framework. The framework is developed on the basis of an analysis of combinations of different risk management and performance management practices/policies. We show how the risk and performance management processes can be improved by proper risk conceptualization and a holistic thinking on how to develop and use goals in the organization, how to balance different concerns, and consider the need for agility – “sensitivity to operations”, as well as how to give weight to vulnerabilities, resilience, and antifragility.