As water distribution infrastructure ages, utility managers must weigh the benefits and costs of pipe repairs against those of replacement. Although models have been proposed to help managers make these decisions, they have not been able to incorporate the environmental and geographic factors that influence infrastructure condition. This article introduces a diagnostic tool that uses system data and pipe break records to help managers identify regions across the network that contain aggressive environments and that may be most prone to failure. The aggressivity index (AI) is an indicator based on historical network performance. Spatial disaggregation is used to assess variability within the network; observed break data are used to infer variable aggressivity across the domain. The AI enables current and potential influences of aggressive environments to be factored in without the need to explicitly identify and measure physical properties that may influence degradation of cast-iron pipe networks. Development of an effective pipe replacement schedule is impossible without insight into the current and future state of deterioration. For systems with a low rate of pipe failure, network monitoring or quantification of influential factors may be almost as expensive as pipe replacement. The AI provides an alternative to costly monitoring-based approaches to main replacement and enables utility managers to compile an efficient replacement schedule that targets pipes in specific areas. Includes 26 references, table, figures.