Spill response is a complex operation that demands the consideration of a great number of varied interests. The planning of operations during a spill event requires an estimate of the future distribution of the pollutant. These are typically obtained by computational algorithms, database references, numerical modeling, or more generally the techniques of trajectory analysis. Since the results of the trajectory analysis are a critical factor in the formulation of operational decisions, the consequences of uncertainty in the forecasts must be analyzed in terms of the response activities they must support. The uncertainty in the forecast results from trajectory analysis must be evaluated in the broadest possible sense. Beginning with the way to solve hydrodynamic flow equations in a sparse data environment, then proceeding to models of geophysical forcing which are the result of additional forecasting, and thus are also uncertain. Finally the contribution of the trajectory analysis to the chain of decision logic that is actually used to formulate response must be considered. Once the uncertainty associated with trajectory analysis results is understood, a use strategy can be formulated on how best to present and use the information. Operations research and game theory methods suggest that ＇minimum regret＇ strategies provide a powerful and understandable procedure for the delivery of forecast information into the spill response system. A digital standard has been developed for implementing this ＇minimum regret＇ strategic approach and has been operational for nearly three years. During this time the response community has used it on over 100 spills and drills with a high level of acceptance.