Research suggests that using data driven solutions in policing strategies improves the quality of service provided by the police department. Unfortunately, many police departments, including the Denton Police Department, do not use their spatial data to inform beat zone placement. Analysis of the current beat zone configuration found that there are disparities in the workload, as measured by number of calls for service, between beat zones. Further, there was also a statistically significant difference between the median response times across all the five beat zones in Denton. This means that the median response time varies depending on where the call for service originates. Using readily available data, these police departments can apply methods such as UPAS to improve the quality of service provided by the department. UPAS is a deterministic algorithm that produces a given number of contiguous spatial partitions of approximately equal population size; in this case, calls for service are substituted for population. Although this algorithm was originally developed to create solutions for bio-terrorism response planning, it has been applied to the problem of creating beat zones of roughly equal workload in this research. I have shown that this algorithm results in a beat zone configuration that significantly reduces the difference in workload between the busiest and least busy beat zone (~94% reduction). Assuming an equal distribution of resources across beat zones, having approximately similar workloads should lead to fewer disparities in quality of service.