Introduction In recent years, the idea of predictive policing, or the use of statistics and data to make policing decisions, has become widely popular in the United States. As police departments faced reduced budgets, improving efficiency in how they work to prevent crime is of great importance (Goode, 2011). However, predictive policing also create a focus on accountability, which has caused some police officers to respond negatively to such pressures (Willis, Mastrofski & Weisburd, 2003). The purpose of this paper is to briefly examine predictive policing and how tools such as COMPSTAT allow police departments to respond more efficiently to criminal activity.
Information Technology vs. Random Patrols Before discussing specific issues involving the use of COMPSTAT as part of predictive policing, it is important to compare and contrast the use of information technology as a way of optimizing police department performance with the more traditional use of random street patrols. The use of information technology applications and performing random street patrols are actually similar because both methods of identifying and responding to crime are intended to examine the events and conditions that exist in a particular area so that criminal activity can be prevented before it actually occurs (Bratton & Malinowski, 2008). In essence, regardless of whether information technology applications or random street patrols are used, the overall goal is to be positioned in a way that fast responses to criminal activity can occur, but also that crime might actually be stopped before it occurs. However, an important contrast between the use of information technology and random street patrols involves the way in which resources are used. With the use of random street patrols, the ability to prevent crime is largely based on personal feelings about whether crime may