Ride Along: Using Simulation To Staff The Ithaca Police Department

In this work, we combine data science, queueing theory and stochastic simulation into an analytical framework to examine the operations of the Ithaca Police Department (IPD) and develop novel solutions that address recent staffing shortages of the IPD. With 3 years of IPD call data, we construct and simulate a novel multiple-dispatch queueing process for modeling the IPD's operations. Unfortunately, using the data alone does not capture the real dynamics of IPD's operations, which made it necessary to augment the call data with qualitative assessments from police ride-alongs. Our analysis augmented with ride-along assessments accurately replicates metrics such as emergency response time and officer utilization. Although it is difficult to fully capture the claimed strains on the department through data alone, hiring additional officers should make an observable improvement in the performance of the IPD.