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Data-Based Analysis Approach in Preventing Crime at Dallas Police Department Essay

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Updated: Jun 8th, 2022

Preventing crimes has recently become the primary objective of the Dallas Police Department. Due to the violent crime spike, at the beginning of 2020, Dallas Police Chief U. Reneé Hall was demanded to present a plan to reduce violent crime plan (Jaramillo, 2020a). However, the recent reports show that despite implemented measures, the number of aggravated assaults has only risen, while the number of murders has even exceeded the last year’s statistics (Jaramillo, 2020b). These results show the inefficiency of the crime prevention program and call for implementing new strategies.

The Dallas Police Violent Crime Reduction Plan includes long-term and short-term measures aimed at crime prevention. It is said to be “data and intelligence-driven” and, among other initiatives, presupposes developing more effective methods of identifying high-risk zones and individuals (Hall, 2020, p. 1). Moreover, it presupposes creating a new Intelligence Led Policing Division that would comprise of already-existing units along with a new Real-Time Crime Center (Hall, 2020). However, according to the Dallas Police Violent Crime Reduction Plan, the newly established division’s main objectives are mainly improving the coordination and sharing of information (Hall, 2020). While it is also essential to ensure the relay of information, “developing and maintaining a strong analytical capacity within police departments” is of much more vital importance (Braga, 2015, p. 20). The main objective of the proposed approach, in contrast, is to enhance the effectiveness of the analysis and research functions within the Intelligence Led Policing Division.

The proposed strategy fits into the supporting structure of environmental criminology that deals with analyzing crime event patterns. This theory is concentrated on preventing crimes by forecasting possible scenarios based on various data. As Wortley and Townsley (2016) note, “environmental criminologists look for crime patterns and seek to explain them in terms of environmental influences” (p. 1). Having a highly developed research center would potentially address some hard-pressing challenges.

First, it would allow making hotspots areas more precise, resulting in even more effective resource allocation. As different crime types tend to cluster in space, the common practice of defining crime hotspots has been used by the police. However, having a highly developed research center would allow the implementation of other methods as, for instance, incorporation of a temporal factor in crime prediction modeling (Catlett et al., 2019; Zhang et al., 2019). This will decrease the time police patrols spend at one location and increase the effectiveness of police resources’ deployment. Moreover, it would be useful to acknowledge other research trends that have been emerging recently. Some of them are the offender mobility research on crime trips and movements, geographic profiling, sexual assault patterns.

Finally, having a stronger concentration on data-based analysis would pave the way for improving the police work organization that is now focused on responding and arresting. The shift from “handling incidents to addressing problems” (Wortley & Townsley, 2016, p. 252) would improve the agency’s image and redefine the meaning of policing. This factor is essential nowadays as ever, as the Dallas Police Department is heavily criticized for being ineffective.

The implementation of a data-based analysis approach will likely prevent numerous crimes and improve the effectiveness of crime-solving. It would allow to change the existing system of crime reduction and facilitate available police resources. Instead of expanding the police force, the strategy is to create conditions for a more tactical approach based on tangible metrics and insights and lead to better crime rates and crime detection rates.

References

Braga, A.A. (2015). Crime and policing revisited. U.S. Department of Justice. Web.

Catlett, C., Cesario, E., Talia, D., & Vinci, A. (2019). Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments. Pervasive and Mobile Computing, 53, 62-74. Web.

Hall, R. (2020). Violent crime reduction plan. Dallas Police Department. Web.

Jaramillo, C. (2020). The toll: Tracking homicides in Dallas in 2020 after last year’s high murder number. The Dallas Morning News. Web.

Jaramillo, C. (2020). Violent crime is up in Dallas but city officials at odds on best way to reduce it. The Dallas Morning News. Web.

Wortley, R., & Townsley, M. (Eds.). (2016). Environmental criminology and crime analysis. Routledge.

Zhang, Y., Siriaraya, P., Kawai, Y., & Jatowt, A. (2019). Time and location recommendation for crime prevention. International Conference on Web Engineering, 47-62. Web.

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