Roger Flage and Tore Askeland’s paper “Assumptions in quantitative risk assessments: when explicit and when tacit?” has been published in Reliability Engineering & System Safety.
- The paper describes a formal set-up for conceptualising risk assessment assumptions.
- The set-up includes a risk description/metric and a typology of uncertain quantities.
- The set-up also defines and distinguishes explicit and tacit assumptions.
- An example involving an offshore oil and gas platform illustrates the set-up.
- A procedure for transforming tacit assumptions into explicit ones is described.
In quantitative risk assessments, several explicit assumptions need to be made, to compute the risk metrics addressed. Such assumptions may, for example, relate to the number of people exposed to specific hazards, to the reliability of safety systems, or to the response of the system exposed to the hazards. In addition, come potential tacit assumptions, for example, when making a probability judgement about an event to occur. The probability judgement is based on some knowledge – which essentially captures data, information, and justified beliefs – and here tacit assumptions may exist, even if explicit assumptions have not been formulated: for example, a belief about how the system works. The probability and resulting risk metrics are conditional on this knowledge including these assumptions, and the strength of this knowledge and the ‘risk’ related to potential deviations from these assumptions needs attention. This paper discusses the concept of a risk assessment assumption, the main aims being to clarify the issues raised and to provide guidance on how to formulate the background knowledge to distinguish between explicit and non-explicit (tacit) assumptions. The paper thus provides a sharper conceptual basis for addressing such assumptions, and also some recommendations for dealing with these in practice.
Flage, R. & Askeland, T. (2020): Assumptions in quantitative risk assessments: when explicit and when tacit? Reliability Engineering & System Safety, Volume 197, May 2020, 106799. DOI: 10.1016/j.ress.2020.106799. [intranet]