Due to the increasing occurrence of disruptions across our global society, it has become critically important to understand the resilience of different socio-economic systems, i.e., to what extent those systems exhibit the ability both to resist a disruption and to recover from one once it occurs. In order to characterize this ability, however, one must be able to quantitatively measure the relative level of resilience that a given system displays in response to a disruptive event. Such a measurement should be easily understandable and straightforward to implement, but it should also utilize a consistent frame of reference so that one can properly compare the relative performance of different systems and assess the relative effectiveness of different resilience investments. With this in mind, this paper presents an improved approach for measuring system resilience that supports better decision making by providing both consistency and flexibility across different contexts. The theoretical basis for the approach is developed first, and then its advantages and limitations are illustrated in the context of several different practical examples.