A feature increasingly utilized in clinical trial practice is to allow a study to stop early when it seems unlikely to achieve its primary efficacy objectives. This is commonly referred to as stopping for futility, and can be motivated by ethical and financial considerations. A number of methods for addressing futility have been described in the literature, including rules based upon conditional power, predictive probability, beta spending functions, and others. We consider futility stopping from the point of view of quantifying and providing an objective sensible balance between risks of incorrect decisions (e.g., stopping trials which should continue, and continuing trials which should stop), and discuss how specific considerations within a trial can lead to choice of a sensible scheme. This approach is not specific to any particular scales in the literature such as those just mentioned, and we describe interrelationships among criteria expressed on different scales. As futility may be evaluated multiple times in a long-term trial and the amount of information available at scheduled interim analyses may be difficult to predict in advance, we present a specific optimality criterion and discuss which of the familiar scales tend to produce schemes simple to describe and implement, and with better behavior across different timepoints at which futility might be evaluated.