Introduction
In most aspects of technical communication, the concept of predictive policing has become an unavoidable issue of concern. Predictive policing refers to police tactics that use the information and advanced psychoanalysis to formulate predefined preventions (Willis, Mastrofski & Weisburd, 2003).
Advantages of IT applications and random street patrols by the police
The application of IT and random street patrols to optimize the performance of police departments require a sense of human intelligence and constant involvement of manpower. According to Manning (2008), the application of those methods enhances the reduction of crime at different levels. The two methods help in determining efficiency and cost-effectiveness in monitoring patrols. The two approaches offer optimal solutions to difficult policy decision-making processes. The application of Compstat was not done as per the original intentions of its innovators. This is because it was seen as a means of reinforcing the original aspects of police patrols, bureaucracy, control, and authoritarianism (Turban & Volonino, 2011). Random street patrols neither encourage information sharing nor bolster effective investigations. This makes it difficult for the police to formulate a unified vision. Tracking the police performance in random street patrols is equally difficult as police departments are compelled to use situations of the past in predicting current incidences of crimes. On the contrary, information technology based on policing enables the police to address unique situations when predicting criminal activities, thus encouraging accountability of human resources in police departments (Manning, 2008).
Unlike in the random police patrols where departments are not connected and hence information is not cross functional, information technology based police patrols enhance focus of the police on the bigger security picture and quick adoption to changing security situations in the society. Although random street patrols by the police are crucial, they are rarely proactive. Proper feedback mechanisms exist in random police patrols. These ensure that incidences of repeated crimes are minimized (Turban & Volonino, 2011).
Information systems’ security enhancement mechanisms are easy to integrate, thus making police practices more efficient and cost effective. This is due to the easy and timely access to information and effective communication through the use of an integrated information infrastructure.
Compstat’s implementation of IS functions
The application of Compstat is based on the understanding that the profession of a policeman is result-based and that it requires high levels of efficiency, reliability, timeliness, and cost effectiveness.
Input
Selection of key objectives, use of timely and intelligent objectives and understanding of progress are key aspects of the manner in which Compstat implements its input function. As Manning (2008) puts it, visibility, timeliness, accuracy, completeness and availability are vital aspects of Compstat‘s implementation of input.
Processing
By selecting among three to five disorder based goals to be realized within a predefined time, crime data and citizen input are analyzed to establish their level of efficiency. Objectives of reduction of policing should never be expressed as a fraction or percentage of the total crime level. This also ensures that rapid deployment of resources to the scene of crime is also done. Thus, the problem is addressed before it escalates. The processing also involves constant follow-up and, ensures that the assessment of the problem is done by using of effective and reliable schemes. Directing and controling crime are vital aspects of crime control.
Output
Focus on key crime challenges, use of streamlined strategies, avoidance of confrontation and brain storming ensure that rapid deployment of output enhances implementation of Compstat. The information system’s output function is based on understanding that the success of a Compstat system can be measured by the lack of crime, rather than the use of crime statistics.
Feedback
Instant tracking of criminal offences, immediate monitoring and follow-up of crime, deployment of resources, and unwavering follow-up underlie how Compstat implements the feedback function of the information system. As Turban and Volonino (2011) put it, this function encourages police departments to seek better solutions if a given alternative fails to yield the intended results.
Faster response to crime
By integrating crime mapping and database systems, information systems such as Compstat have enhanced communication efficiency, reliability of crime reporting mechanisms, and also streamlined means of identifying repeated crimes. The fact that Compstat enables proper evaluation of the performance of criminal investigation departments means that information systems also help streamline police departments’ operations (Turban & Volonino, 2011).
The use of information systems in police departments encourages accountability and formulation of reliable and quick responses to situations of emergency. According to Siegel (2009), information systems encourage uniformity in crime response thus enabling police departments to have a better understanding of more reliable crime response strategies preferred. Reduction of crime and social problems by harmonizing various law enforcement units that work alongside police patrol units enhances effective law enforcement. This helps to eliminate unnecessary competition in the police force and any possible resistance to the adoption of information systems. As a means of responding to crimes better, information systems encourage teamwork by compelling every security sub-group to consult and utilize integrated information management systems. Manning (2008) provides that information systems have been very vocal in eliminating “group thinking” and, at the same time, encouraging open minded solutions that did not focus on maintaining the status quo.
Compstat’s SWOT analysis
Strengths
According to Turban and Volonino (2011), Compstat has the ability to enhance efficiency, creativity and eliminate redundancy in the crime management process. This is effectively done by collecting, analyzing and mapping crime related data and other police performance measurement criteria.
Weaknesses
As a weakness, lack of proper conceptualization of crimes can lead to underrating some crimes and undervaluing crime levels. Compstat’s crime reducing impact has been minor due to the increasing reforms in the random police patrol programs. This approach to crime management discourages police officers from documenting crime reports in order to portray the random patrol approach as being an effective means of reducing crime (Turban & Volonino, 2011). Under-reporting of serious crime incidences is evidently a major challenge posed by Compstat.
Opportunities
Incorporation of more people friendly policing strategies is vital for enhancing security. This is an opportunity that ensures that both technological and people-centered policing approaches are employed in enhancing efficiency and cost effectiveness of policing endeavors. There is an opportunity to implement Compstat through organizational success and strategic predictive policing.
Threats
For a police department that intends to implement predictive policing, it is crucial to understand that this approach can lead to redundancy of human resources and subsequent failure to address human aspects of crime detection and management. Should the police departments’ decision making systems be devolved and streamlined, they can render the most aspects of information systems outmoded and cost ineffective. Compstat tends to encourage bureaucracy by eliminating creativity and innovativeness in dealing with crime as a predetermined information system guides the entire crime detection and management process (Siegel, 2009).
Conclusion
Information systems, Compstat and predictive policing highly contribute to a decrease in crime in the society. It is evident that the use of geographical information, strategic law enforcement agencies and systems, timely identification of crime hotspots, and effective management of crime data and algorithms are crucial mechanisms of effective predictive policing.
References
Manning, P. (2008).The technology of policing. Crime Mapping, Information Technology and thee rationality of Crime Control.USA: New York University Press.
Siegel, L. (2009). Introduction to criminal justice.12th Ed.USA: Wadsworth, Cengage Learning.
Turban, E., & Volonino, L. (2011) Information technology for management (8th Ed.). Hoboken, NJ: John Wiley & Sons.
Willis, J. J., Mastrofski, S. D., &Weisburd, D. (2003).Compstat in practice: An in-depth analysis of three cities. Police Foundation.USA: Cengage Learning.