Consequence and utility modeling in rational decision making

Offshore design and risk assessment are typically marked by far-reaching choices and important one-time decisions. Decision analysis involving large structures, sensitive environments, and difficult operations, requires a very careful formulation of utility and consequences. It is shown in this paper that one of the most important shortcomings of such analyses stems from an incomplete definition of the system, and from the failure to include various "Follow-up" consequences. "Follow-up" consequences are, generally speaking, triggered by extreme losses, such as excessive business losses, consequences from unexpected cascade effects, collateral and indirect losses, or other intangible losses. The non-inclusion of such losses occurs either voluntarily or involuntarily. Often the identification and the valuation of follow-up consequences can be prohibitively difficult. For such cases, it is possible to use a simple model based on risk aversion to the consequences associated with extreme discrete hazards during the lifetime of a system. This model is developed in the framework of a lifecycle utility optimization. To add practical value to this model, we also introduce the concept of a Bayesian updating of utility functions. Since utility functions are all about expressing the preferences of expert decision makers, we refer to the Bayesian parameters as "preference" parameters. The paper shows that the approaches developed lead to better and more risk-consistent decision making. An illustrative example is given in the paper, highlighting the significance of the findings.