Predictive Policing
Compare and contrast the application of information technology (IT) to optimize police departments’ performance to reduce crime versus random patrols of the streets.
For many decades police departments have had to rely on their gut instincts on where they should patrol. While this may work for the experienced police officers in smaller towns, but this process does not work well in the large populated areas. Adequately responding to criminal activity becomes more troublesome when seconds count to capture criminals and save the lives of their victims. In the early 1990’s programmers were able to develop software that tracks and provides timely analysis of criminal activity called COMPSTAT (COMPuter STATistics). This analysis has enabled police departments to tailored their responses to the data and rapidly deploy officers and resources to deter criminal activity. An accountability structure is vital to ensuring the analysis is acted upon and the responses are implemented properly and assess whether their responses were effective in reducing crime and disorder (Weisburd, Mastrofski, McNally, Greenspan, & Willis, 2003). COMPSTAT’s success has been widely touted, and its model has been broadly shared throughout police departments across the United States’. The COMPSTAT tool has enabled police departments to not only predict crime but deter crime before it occurs and properly assign officers to quickly respond to the threats when they occur. Relying on