Law enforcement is a never ending series of effort to maintain civility among the general population. The majority of law enforcement is by default reactive. A person cannot be held accountable for breaking the law until after they have broken it. However in recent years as technology has continued to grow police have tried to move into a more proactive role while still allowing people to enjoy personal freedom and the right of presumed innocence. As part of the movement toward proactive policing, law enforcement are utilizing technology called predictive policing.
With this system officers gather data and analyze it for patterns in order to understand the nature of a problem. The officers will then create strategies and tactics designed to prevent or mitigate chaos. They will then continue to evaluate the resulting data and make changes as needed to improve performance. The predictive policing system is designed to use disparate data and such as general information, geospatial technologies, and evidence based intervention models to reduce crime and improve safety. The second aspect is applying advanced analytics to the various data sets.
This two pronged approach used in conjunction moves law enforcement into the realm of predicting what and where something is likely to happen and allowing deployment of resources accordingly. This predictive approach does not and will not ever replace traditional policing. What it does instead is to enhance existing approaches such as community policing, hot spot policing, problem-oriented policing, and intelligence led policing. To understand how predictive policing works one should look at computer models used in the business sector to anticipate how market conditions or trends will evolve over time.
For law enforcement purposes, it’s used more on anticipating likely crime events and providing actions useful to prevent crime. Using models supported by prior crime and environment data such as parolee populations, economic conditions, and demographic trends to inform different kinds of interventions help police reduce the number of crime incidents. One such predictive policing tool that is currently being used is a system called CompStat. As enforcement agencies have adopted computerized records systems and geographical information systems, their ability to analyze and assemble data regarding crime has soared.
The technological capabilities are growing faster than law enforcement s capacity to understand and react to all the potential ethical implications. Utilizing predictive policing allows law enforcement to visualize, measure, and define concentrations of offenders. One outcome of that technological mapping is predicting that a certain location may experience an increase in crime the officers may be tempted to apply previously successful strategies such as zero-tolerance, saturation patrols, field interrogations, and highly visible arrest sweeps. The problem however with predictively allocating resources to areas is the ethical quagmires that might be triggered.
Those tactics create significant risk of differential policing based on race, age, national origins, and other variables. Policing young men in poor neighborhoods is a recipe for ruining community relations between police and the community, perceived lack of procedural justice, along with accusations of racial profiling, and a threat to police legitimacy. CompStat is an organizational tool for police departments and was not originally a software package in its original form. It has evolved however to include computer systems, software, and other implements collectively called CompStat. There are four core components of CompStat and those are timely and accurate intelligence, rapid deployment of resources, effective tactics, and relentless follow up.
CompStat is a multifaceted system used primarily for managing police operations. In police organizations, it is manifested in recurring meetings, during which the agency’s performance indicators are critically reviewed for improvement opportunities.
When viewed strictly from a information system standpoint CompStat can be broken down into 4 categories; input, processing, output, and feedback. The input aspect of CompStat is the easiest area to identify it is the gathering and analyzing of real time and historical data. Data types include personnel sick time, use of force, civilian complaints, and accompanying municipal liability. That is just data from the officer’s perspective; the system also takes in and analyzes geographic data, environmental criminology, economic conditions, and historical inter-departmental criminal data.
All of these various sources of seemingly disparate data is gathered and interpreted by the system and then processed back out to the law enforcement agencies as computer generated data that is as close to real time as possible. The data is rendered in various formats for review such as charts, graphs, command profiles, and criminal snapshot reports. It is then up to the leadership to analyze the processed data and allocate appropriate resources to identified problems. The CompStat process is a information driven system without accurate and timely data, the management systems will be ineffectual.
Feedback of the system can come in the form of changing internal department operations running smoothly or the ability to be able to immediately identify problem areas and determine the reason for the issues and correct them. While CompStat is less of a revolutionary computer and software system and more of a management accountability philosophy, it has like all things strengths and weaknesses. A comprehensive look at CompStat reveals a detailed analysis of the system.
Several strengths the system offers are data being available in real time; the police work is performed in a more efficient manner, a by-product of streamlining resources and performing work more efficiently is that the cost of preventing crimes decreases. Another strength is that because the data is non-biased it helps eliminate any possibility of discrimination and doesn’t impugn upon any civil rights. There has yet to be any system created that works perfectly and the CompStat is no exception; it too has weakness that have to be recognized and dealt with accordingly. It has to framed within the limited budget of the law enforcement agency its being used by, the leadership has to overcome the inherent resistance of the officers what can be seen as an indictment on how they perform their jobs to change.
Also depending on how it’s implemented there can be issues if there is a lack of strategic priorities with no clear vision. CompStat while not a perfect system by any means has many areas of opportunities that can greatly increase its effectiveness. It can help facilitate greater communication between interagency departments as well as between two different agencies. It also is a well-defined system that helps retrain personnel to think efficiently and more flexible.
The system provided the opportunity to develop lasting regional partnerships and raise expectations regarding the quality of data shared. A threat that must be managed is the potential loss of the community’s trust in law enforcement due to less empathic reactions. References: Casady, T. (n. d. ). Police Legi? macy and Predic? ve Policing. Retrieved October 19, 2014, from h$p://www. nij. gov/topics/technology/maps/Documents/gps-bulle? n-v2i4. pdf?
Redirected=true Predic? ve Policing. (n. d. ). Retrieved October 19, 2014, from h$p://www. nij. gov/topics/law- enforcement/strategies/predic?ve-policing/Pages/welcome. aspx Police Chief Magazine – View Ar? cle. (n. d. ). Retrieved October 19, 2014, from h$p://www. policechiefmagazine. org/magazine/index. cfm? fuseac? on=display_arch&ar? cle_id=1859&issue_id=82009 Compstat in Prac? ce: An In-Depth Analysis of Three Ci? es. (n. d. ). Retrieved October 19, 2014, from h$p://www. policefounda? on. org/content/compstat-prac? ce-depth-analysis-three-ci? es Goode, E. (2011, August 15). Sending the Police Before There’s a Crime. Retrieved October 19, 2014, from h$p://www. ny? mes. com/2011/08/16/us/16police. html? _r=0.