Comparative statistics/Computer statistics or Comp stat is the process through which crime data and other police performance measures are collected, analyzed and mapped on a regular basis with the aim of enhancing performance of police managers by holding them accountable on the basis of these data. In other words, it is a strategic system through which information on crime and other quality of life issues is collected and feedback provided. This process was first introduced by transit police officer Jack Maple and Chief William J. Bratton in 1994 at the New York City Police Department. Since then, other cities including Los Angeles have emulated the paradigm that helped set precedence for modern policing. Comp stat in New York and Los Angeles is implemented and evaluated in a number of ways.
Appropriate implementation and evaluation of Comp stat enable political entities to inspect police departments for performance measures. Hence, police managers whose performance is questionable can be easily identified and correctional measures instituted to ensure accountability and efficient allocation of police resources. The principles of accountability and inspection are entrenched in this process together with close collaboration, auditing methods, and mentorship. Comp stat provides an early warning system for the identification of emerging crime trends and patterns by providing accurate and timely intelligence to police officers across the board (Swanson et al, 2012).
Comp stat has transcended traditional police methodologies or tactics of solving crime at a superficial level. Traditionally, a suspect or actual culprit would be apprehended and bundled into police custody, and period; the problem would have been “solved” (Walsh, 2001). Social, cultural, environmental factors among others that nurtured the crime would be conveniently neglected meaning that the police would have to keep making similar arrests over and over again. Apparently, these strains available resources allocated for combating crime. Therefore, with comp stat, effective tactics that take crime seriously are employed in combating crime.
Comp stat equips police officers with appropriate intelligence to enable them to strategically respond to service calls (Walsh, 2001). Response can be in form of anything ranging from sting operations, plain clothes or uniformed officers or non traditional decoys. Apart from rapid deployment, consistent and relentless follow-ups and assessment of crime trends and patterns is carried out. Review of past tactics helps reveal what worked and what did not work. This provides police departments with results that will eventually help police managers to evaluate strategies to be implemented and those to be discarded.
Evaluation is done on a weekly basis. NYPD dispatches personnel from 12 transit districts and nine police service areas to compile crime reports (Swanson etal, 2012). The reports describe police activities, criminal complaints, crime patterns, significant cases, summons issued, and arrests made. Such data is then submitted to the chief of the department’s Comp Stat unit. Here, the data is assembled and uploaded into a city wide database. Afterwards, the data is analyzed through appropriate computer software in order to generate a concise weekly Comp stat Report depicting performance indicators such as arrest activities, crime complaints etc. Moreover, weekly accountability meetings that enhance the flow of information between commanders of operational units and agency’s executives are held. Information concerning quality of life and prevalence of crime is discussed during such meetings. During these meetings, community policing strategies are designed to deter people who interfere with quality of life by engaging in minor offences. Such offences may range from loud music, prostitution, public urination, public drinking to name just a few.
Community-oriented policing strategy refers to a policing philosophy or strategy that puts emphasis on the interaction between communities and how this can be used to contain crime and allay fears as members of the community help identify culprits and detain vandals (Walsh, 2001). In a nutshell, communities are encouraged to form partnerships between each other and other government agencies, private businesses, media, NGO’s etc, and come up with problem-solving ideas in order to reinforce traditional aspects of law enforcement in crime prevention. The mnemonic SARA refers to a policing strategy implemented through comp stat by police managers to educate members of the community on the four steps involved in the making of decisions during the process of problem solving.
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The mnemonic SARA stands for Scanning, Analysis, Response and Assessment (Landy & Conte, 2004). Scanning enables individual to determine problems through communication and personal experience. The individual may communicate with private agencies, residents, businesses, employees, officers, public agencies etc. It can also be through personal experience with behavior that is well known to the community or the police, location or an activity. An incident that occurs more than once and is similar in terms of time, location, person or behavior is deemed to be a problem and should be reported immediately to appropriate police agency. Analysis helps an individual to create a custom made solution to the problem if he or she can be able to connect the relationship between location, suspect and the victim. Response is only as good as the analysis. It helps an individual determine the desired goal i.e. eliminate the problem; reduce the harm caused by the problem etc. Assessment helps individuals determine whether the problem reported to police was solved.
References
Landy, F. and Conte, M. (2004). Work in the 21st Century New York, NY: McGraw-Hill.
Swanson, R., Territo L., and Taylor, R. (2012). Police Administration: Structures, Processes, and Behavior, 8th ed. Upper Saddle River, NJ: Prentice Hall Publishing.
Walsh, D. (2001). Comp Stat: An Analysis of an Emerging Police Paradigm. An International Journal of Police Strategies and Management, 24 (3), 347-363.
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