Predictive policing refers to the collection of data from different sources, subjecting the data to analysis and applying the results of the analysis in order to predict the emergence of crime, prevent its occurrence and ensure effective response to crime that may occur in the future. It relies on sophisticated technology in order to analyze the data and pre-empt the commission of crime. Police officers are expected to be pro-active rather than reactive to the occurrence of crime (Taylor, 2011). Law enforcement is shifting from figuring out what has happened after the commission of crime to anticipating what will happen before it. The most essential feature of predictive policing is that police are able to identify crime trends and patterns, about which they did not know before. Predictive policing is not meant to eradicate the previous police technique and tactics; it is intended only to complement them (Roger, 2012). It is hypothesized that the ability to predict crimes provides the Police Department with better opportunities to detect and respond to crimes, ultimately enhancing public safety.
Predictive policing is based on five major tenets: proper allocation of resources and staff on patrol; studying crime patterns and identifying the likely time or location of future crime; identification of individuals who are likely to commit an offense; assessment of vulnerability and threat; mapping and planning of cities and neighborhoods among others. This paper analyzes predictive policing in depth comparing it with random patrols and describes how COMPSTAT fulfills the basic functions of information system. It examines whether COMPSTAT leads to a faster response to crime and conducts a SWOT analysis of predictive policing.
The Application of Information Technology versus Random Street Patrols
The application of information technology (IT) to optimize the police departments' performance in order to reduce crime is a core feature of predictive policing. Compared with random patrols on the streets, the application of information technology is more effective. Incorporation of information technology gives officers the leverage of information-based strategy at the approach to the matters of crime unlike random patrols where officers rely on sheer luck and instincts (Uchida, 2010). Therefore, public safety is more enhanced when information technology is used as the knowledge is used to quickly prevent and respond to criminal activities.
Officers are also in a position to analyze the patterns of unruly or illegal behavior and, thus, are able to use effective policy. The use of information technology also saves the time spent by patrol officers on the street and cuts the expenses used by them (Rogers, 2012).While during patrols, officers may be allocated to areas where their presence is not needed, information technology enables police resources to be allocated where they are required to prevent crime and ensures a heavy police presence in those specific areas securing a reliable response. However, whereas street patrols make certain that all areas in a police district are covered, the use of information technology may lead to the neglect of places where criminal trends have not been identified, and offenders may shift their activities to such places (Uchida, 2010).
How COMPSTAT Implements the Four Basic Functions of Information System
COMPSTAT is a short-form of computer statistics or comparative statistics. It is a strategic management approach used by police to reduce crime. It was originally created by the New York Police Department. Crime maps and statistics are used to identify the areas that are the most vulnerable to criminal activities. COMPSAT fully implements the four basic functions of information system.
The input involves acquisition of accurate and timely intelligence. Police officers in a department use revolutionary methods of collecting intelligence and information about criminal activities in their area (Cox et al., 2011). This includes the use of advanced techniques and computer software such as Geographic Information software, exploratory graphs and artificial intelligence.
The processing function is implemented through effective tactics, by which crime incidents and emergencies are not treated as isolated incidents. Other factors considered during a response to crime are the social-environmental issues that could have contributed to the crime. This holistic approach ensures effective processing of data and information. Afterwards, officers are able to analyze the data and identify the likely criminal occurrences and those, who made them. The obtained data and information is then fed into a central integrated database (Taylor, 2011).
The output involves response measures such as rapid deployment. In emergency situations, police bosses have to struggle with the deployment of officers. However, COMPSAT enables them to allocate personnel resources strategically based on crime patterns and recent occurrences and also allows allocating the task to the most qualified officers whereas the feedback option is seen through relentless follow-up and assessment (Cox et al., 2011). The reason is that the efficiency of the police in reducing crime is constantly assessed through crime maps and statistics. The rate depends on the particular police department, and it can be weekly or monthly. Unsuccessful tactics are then dispensed and replaced with more innovative ones.
How Information Systems Have Enabled a Fast Response to Crimes
Information systems such as COMPSTAT have helped police departments to respond to crimes faster through several ways. Police chiefs can allocate resources and personnel more effectively based on intelligence acquired through such information systems and, thus, are in a position to deploy faster. They are also able to respond to incidences of crime efficiently and gain the public trust (Roger, 2012).
Information systems are used to detect fraud and identity theft through the use of advanced statistics. Drug activities and cartels including the activities of drug-lords and their cronies are monitored by such systems. Thus, police can respond faster when the master-minds try to put their plans into actions because they already have the blue-print. Police are also able to provide quick relief in case of emergencies or disasters as information systems can detect the occurrence of these events before they happen (Uchida, 2010).
Police department cannot apply predictive policing out of the blues or without a policy framework. Such a department may wish to consider its strengths, weaknesses, opportunities and threats (SWOT analysis). The strengths of predictive policing help prevent crimes; police are able to respond faster, and public safety is enhanced. The accuracy of forecasts improves with the level of data collection. Hence, the more data police department is able to collect, the higher is the level of efficiency (Taylor, 2011). The weaknesses are that it requires hiring of specialists and infringes on the individual’s right to privacy, as well. In addition, officers can intervene in the information system and alter data or provide incorrect information.
There are many opportunities in predictive policing such as the introduction of more advanced software and statistical analysis methods. Police department may boost public confidence due to the reduction of criminal activities. Since technology develops at a very fast rate, information systems will become easier to use and more efficient (Roger, 2012). The threats are that criminals may hack into these information systems and access crucial and confidential data. The reduction of personnel may also lead to dissatisfaction among the police officers, who get laid off or those who are rendered redundant.
Prevention of crimes is cheaper and more effective than their solution. Predictive policing is a very significant aspect of crime control, and the model should be replicated in every city across the world. Software upgrades from time to time will improve the efficiency of information systems. However, caution needs to be exercised in such a way that police surveillance does not infringe on the privacy rights and civil liberties of innocent citizens.