The methodology utilized by public sector managers to allocate scarce resources determines the level, efficiency, and effectiveness of service delivery. These decisions are influenced by a myriad of factors, not the least of which is the ideal goal to distribute services in a fair and equitable manner. This ideal becomes problematic if service outcomes are important to public decision-makers, because the level of need for these resources is not spread equally across local jurisdictions. Therefore, when goods and services are located or distributed equally to all "customers," many do not receive enough assistance and others receive more than they prefer. This causes inefficient service delivery that fails to maximize potential positive outcomes with the available limited resources. This is particularly true with the geographic distribution of fire service resources across most communities in this country.This research effort attempts to model the demographic characteristics that drive emergency service demand and workload across local jurisdictions. Specifically, data about demographic characteristics was collected at the Census block group level and compared to emergency response data collected by the Charlotte Fire Department. The findings from this effort are promising, as the bivariate correlation and multivariate regression analyses indicate that economic and structural factors common to all local communities can be used to confidently predict demand and workload on local public safety systems. Measuring these characteristics at the block group level permitted the opportunity to isolate homogenous groups within the population that have risk characteristics associated with more or less demand for these services. These findings provide a solid base to support the development of an alternative model for locating these critical emergency resources according to demand and workload to better meet the needs of individual communities.