On solving decision and risk management problems subject to uncertainty

TL;DR

This paper systematically analyzes strategies for managing uncertainty in decision problems, identifying key properties that enable effective solutions and proposing a framework to improve decision-making under uncertainty.

Contribution

It introduces a set of 14 pivotal properties that characterize decision problems and guides the application of robust strategies, enhancing understanding of problem tractability.

Findings

Many decision problems have pivotal properties enabling solution strategies.

Identification of 14 pivotal properties that facilitate decision-making.

Complex problems under uncertainty can often be surprisingly tractable.

Abstract

Uncertainty is a pervasive challenge in decision and risk management and it is usually studied by quantification and modeling. Interestingly, engineers and other decision makers usually manage uncertainty with strategies such as incorporating robustness, or by employing decision heuristics. The focus of this paper is then to develop a systematic understanding of such strategies, determine their range of application, and develop a framework to better employ them. Based on a review of a dataset of 100 decision problems, this paper found that many decision problems have pivotal properties, i.e. properties that enable solution strategies, and finds 14 such properties. Therefore, an analyst can first find these properties in a given problem, and then utilize the strategies they enable. Multi-objective optimization methods could be used to make investment decisions quantitatively. The analytical complexity of decision problems can also be scored by evaluating how many of the pivotal properties are available. Overall, we find that in the light of pivotal properties, complex problems under uncertainty frequently appear surprisingly tractable.