• Risk ranking;
  • muddling through;
  • risk communication;
  • comparative risk

This article presents a model designed to capture the major aspects of setting priorities among risks, a common task in government and industry. The model has both design features, under the control of the rankers (e.g., how success is evaluated), and context features, properties of the situations that they are trying to understand (e.g., how quickly uncertainty can be reduced). The model is demonstrated in terms of two extreme ranking strategies. The first, sequential risk ranking, devotes all its resources, in a given period, to learning more about a single risk, and its place in the overall ranking. This strategy characterizes the process for a society (or organization or individual) that throws itself completely into dealing with one risk after another. The other extreme strategy, simultaneous risk ranking, spreads available resources equally across all risks. It characterizes the most methodical of ranking exercises. Given ample ranking resources, simultaneous risk ranking will eventually provide an accurate set of priorities, whereas sequential ranking might never get to some risks. Resource constraints, however, may prevent simultaneous rankers from examining any risk very thoroughly. The model is intended to clarify the nature of ranking tasks, predict the efficacy of alternative strategies, and improve their design.