Free predictive policing research paper example

IntroductionTechnology is currently evolving at an alarming rate than its implementation. The departments of police should adopt the use of technology to enable them effectively prevent crime through predictive analysis. Integration of technology based on information system and operations eliminates the outdated and informal pitfalls, thus giving way for easier and faster access to required information. The process of predictive policing emphasizes on operating, managing and developing an integrated information infrastructure. Ideally, this approach leads to the elimination of information technology pitfalls in the police department. The application of IT in police departments leads to neighborhood prosperity irrespective of the limited resources in this century. Globally, police officers have been patrolling estates and streets effortlessly to maintain security.
Comparing and ContrastingComparing and contrasting the use of IT by police departments in fighting crime with random street patrols, is comparative to case studies regarding police departments that have adequately implemented the technology. The documented countries that have embraced the application of IT to curb crime include Virginia, Arlington, Texas, united states and Richmond (Shurkin, 2011). The police departments used data from previous years to anticipate location, time, and nature of future incidents before they occurred. Additionally, the technology aided the deployment of law enforcers in the foreseen areas to dissuade the intended criminal activity. The technology made the police departments respond rapidly in crime locations for preventive missions. IT has the power to capitalize on productivity by creating peace and reducing criminal activities. Predictive policing highlights a reporting system powered by computers, a derivative of IT. This system is a rather new program for fighting crime. The technology is fed by data whereby information implementation and the application of information system (IS) produces a systematic alert report for the police. Therefore, the police departments are able to predict future criminal activities. The computer program has an added benefit to the crime-fighting infrastructure with the most recent crime being automobiles theft, home burglaries among others (Willis, Mastrofski & Weisburd, 2004). Predictive policing has numerous benefits that render patrols irrelevant. The documented predictive policing involves integrated operations and information, cutting-edge analysis and technology, seeing big and clear pictures, adaptability to changes of conditions and linkage to performance. For instance, the technology facilitates resource allocation and patrol staffing, assessment of threat and vulnerability, crowd patrol, analysis of predatory patterns and traffic management among other applications. Willis, Mastrofski and Weisburd (2004) emphasize that the integration of operation and information eliminates the silos, thus permitting timelier and simpler criminal activity information access. The element centers on management, development, integration and operation of a pool of infrastructural information. Some of the drawbacks in police departments before the introduction of IT included isolation of information and voluminous databases that resulted into huge communication breakdowns. The information received by police departments should be cross-functional in nature, and can be obtained by developing proper linkages to the analytical systems of the police. Poor dissemination of information within police department can deter investigation of crime. Therefore, predictive policing is necessary for accomplishing elaborate crime prediction. The highlighted factors outweigh manual police patrols that consume resources such as time and money in fueling the police vehicles and other machinery. Secondly, the elements of having a complete picture provide numerous accurate interpretations. The police interpret a picture to give a collective vision on the anticipated geographical area. The pictures assist in resource allocation and estimation of the required number of skilled law enforcers deployed in the neighborhood or city. Effective dealing with a crime incidence requires the opportunity to gather relevant information applied to the patterns of development in the community. Conversely, patrols eat up the energy and time of law enforcers (Willis, Mastrofski & Weisburd, 2004).
Furthermore, the already available tools and technology in the police departments have boosted the ability of cutting-edge analysis and technology. The linkage to performance provides an efficient performance tracking system that permits valuable forecasting for future crime. Additionally, the available police technology permits the input of police in their own scenarios instead of depending on the traditional patrol approach (Shurkin, 2011). Therefore, the police departments are able to monitor the development of crime trends before they become a threat to the public. The technology also enables the strengthening and management of personnel. Notably, the old-fashioned way of crime prevention never utilized police resources effectively. The Compstat ModelResearch by Shurkin (2011) implies that the technology is a problem-solving model that directs employees to formulate, identify and provide solutions to problems by analyzing the results for effective application. The model consists of four principles that when integrated define crime-driving strategies and create internal procedural efficiencies. The principles are directly applicable in addressing community-based crime problems, internal risk management policies and incidences and quality-of-life. A study by Charlie and McCue (2009) provides that the initial basic function is comparable to accurate and timely analysis because at the base of every activity applies computer-generated and other statistical data gathered close to real time and consequently presented in multiple formats both electronically and in hard copy. The formats mention graphs, charts, crime hotspots and profile of command. The assessment and analysis of the information presented by law-enforcing officials trigger immediate action on the anticipated complications (Shurkin, 2011). The collected information and data on crimes are fed into computer systems. Secondly, processing relates to effective tactics since once the command and the police officers receive the accurate and timely intelligence, they account for the development, creation and implementation of purposeful action plans and crime eradication strategies to better manage crime. Furthermore, the IS output function resembles rapid deployment because formulation of appropriate resources follows the identification of an issue tactically. Therefore, the police department must embark on rapid deployment of the proposed plan to reap results before the target changes position. Similarly, the analyzed data is then ready for formation of an action plan. Lastly, feedback is the function comparable to relentless follow-up and assessment. This is because, by nature, it follows inspection relentless assessment and follow-up. Similarly, a mechanism of feedback is put in place to aid in operational control and monitoring of crime. The increased IT application in police departments has facilitated crime monitoring tools such as a comp stat to provide faster reaction to crime. Information technology has provided information power and increased the intellectual capacity of law enforcers to provide amicable and timely solution to problems. Particularly, the cutting-edge technologies such as spatial analysis and data mining tools enable testing and modeling of various criminal and criminological justice in the police departments (Charlie & McCue, 2009). Additionally, technology allows the prediction of crimes to the neighborhoods and facilitates factors such as target hardening strategies, neighborhood characteristics and community involvement in crime prevention. SWOT Analysis of Predictive PolicingStrengthThis IT application provides informed operational and strategic decisions irrespective of the agency size. The basic principles of the technology have been used by businesses to make product orders. Besides, the technology assists in determining the number of staff required for the business to operate. The same principles apply to the police departments, thus effectiveness and efficiency in the police departments. WeaknessPredictive policing can be difficult to apply to a smaller agency because the smaller agencies focus on less intense crimes. For example, it would be difficult to employ the technology where a gang of 40 robbers related to violent crimes is likely to be in the future (Charlie & McCue, 2009). The seriousness and frequency of crimes are low in smaller police departments than in larger agencies. Therefore, the technology expresses weaknesses in smaller agencies. In addition, there is no definite software available for predicting all the types of crime all over the country and every single time. OpportunitiesThere are numerous opportunities in the development of the software. The software has undergone rapid improvements and is human-friendly. This enables software management and application to grow with the funding of research. ThreatsIt is difficult to purchase the right software and to test it. In addition, it is difficult to create institutional knowledge about philosophy because the technology may not work if the command staff and police chief are the only personnel on board (Shurkin, 2011). Therefore, improper application and management may not assist the police department. ConclusionThe primary objective of police agencies is to fight crime effectively. Therefore, information technology solutions are better placed to solve crime problems. Increased adoption of technology in the police departments enables cost-effective crime solutions globally. The use of predictive policing in the collection of relevant data and analysis for prediction of crimes leads to a broader reduction of crime via new data analysis and comp stat data.

References

Charlie, B., & McCue, C. (2009). “ Predictive Policing: What can we learn from Wal-Mart and Amazon about fighting crime in a recession?” Police Chief Magazine.
Shurkin, J. (2011). Santa Cruz Cops Experiment With ‘Predictive Policing’. TPM. Retrieved October 17, 2014, from http://talkingpointsmemo. com/idealab/santa-cruz-cops-experiment-with-predictive-policing
Willis, J., Mastrofski, S., & Weisburd, D. (2004). Compstat in Practice: An In-Depth Analysis of Three Cities. Police Foundation. Retrieved October 15, 2014, from http://www. policefoundation. org/content/compstat-practice-depth-analysis-three-cities