Intelligence-Led Policing: A Proactive Approach to Combating Corruption

Following the most fatal terrorist attack in the US, legal theorists and practitioners have popularized the new approach, intelligence-led policing, that raised the hopes about addressing the pending issues. The idea behind intelligence-led policing is that raw information at the disposal of the police needs to be involved in analytical processes that would later inform decisions: measures, solutions, and initiatives. Without proper application, information does nothing for those working in law enforcement.

The present paper argues that the discussed approach might be appropriate for decreasing the crime rate in one of the most problematic counties in the United States, Clayton County, Georgia. Unimpeded flow of information and ongoing communication would assist the local police to keep the situation in check. However, arguably, the introduction of intelligence-led policing will take time and effort: it requires staff training and extra equipment. Besides, as any other strategy, intelligence-led policing has its own set of pitfalls and challenges that need to be approached with thoughtfulness and consideration.

Overview

Intelligence-led policing allows for strategic integration of intelligence analysis into the workflow, mission, and vision of the organization. Budhram (2015) defines intelligence-led policing (ILP) as a conceptual framework that revolves around risk assessment and risk management. The strategy hinges on the premise that as any other institution, the police have limited resources at its disposal and it cannot afford squandering them without a second thought. Intelligence-led policing is a data-driven approach that allows the police to gain deeper insights into crime problems and enables them to make informed decisions (Carter & Phillips, 2015).

According to Budhram (2015), one major misconception that many people still hold onto is imagining ILP as shady, covert operations and activities. On the contrary, ILP promotes transparency and accountability as it relies on processes adopted from the business world that help legal workers with resource allocation. ILP facilitates the creation and organization of new knowledge derived from data. Lastly, the framework implies making new decisions based on previous events: it suggests that the police learns from the past and do not make the same mistakes twice.

Intelligence-led policing is not a nebulous framework: in actuality, it is a strategy that yields positive results and proves its efficacy time after time. In Texas, the Austin Police Department has seen a reduction in the violent crime rate, burglaries, and repetitive offenses (Broussard, 2018). The best result logged by the police was a 15% decrease in burglary of vehicles. The ambitious aim that the Austin Police Department has set before embarking on ILP implementation was to identify the 20% of the population that are responsible for 80% of the crime (Broussard, 2018). Apparently, other states have also benefited from the new law paradigm.

Medford, Oregon, has achieved an outstanding clearance rate for all categories of crimes in excess of 80%. By combining ILP, problem solving, and technology, the San Diego Police Department discovered that 16% of gang members in the area were responsible for half of all crimes (Broussard, 2018). As a result, the police were able to target the “hot spots” and reduce the overall crime rates without wasting resources. This real-life evidence suggests that ILP is a viable strategy that can be translated into practice and provide an advantage for the police in Clayton, GA.

Components of the Program

The ILP model is grounded in three focal points: the criminal environment, intelligence analysis, and decision-making. The said points shall become the components of the new policing program in Clayton, GA, as presented below:

  • The criminal environment is not a physical environment but rather an informational space. In regards to a specific issue, the criminal environment encompasses raw, unprocessed, and unstructured data, existing knowledge, patterns, and instructions. Analysts working for legal forces target the criminal environment for data collection – both from public and private sources. At this stage, it is essential that analysts create and maintain various communication channels. It is not exactly feasible nor sustainable to only rely on the data collected by the police itself. To diversify databases, the police might want to enter into memoranda of understanding with businesses and government institutions. After the data is collected, it needs to be distributed to everyone at relevant departments for further assessment and analysis;
  • Intelligence analysis relies on established mathematical and statistical methods for achieving real-life goals. According to Burdham (2015), at present, the most frequently used techniques include:
    • Link charting for demonstrating relationships between entities;
    • Event charting for demonstrating chronological relationships between entities and pinpointing the sequences of events;
    • Commodity flow charting is a crime-specific technique that explores the movement of money and stolen goods;
    • Activity charting for depicting activities constituting a criminal operation;
    • Frequency charting for quantitative data interpretation;
    • Data correlation (simple linear regression, multiple regression, and others) for illustrating relationships between variables, their influence on each other.
  • Decision making is the last component of ILP model that suggest that it needs to be data informed. Analysts can help the police make decisions by predicting events and singling out particular individuals or groups of people with deviant behavior. Another application is identifying “hotspots” for crime so that the police could allocate its resources accordingly.

Common Crimes

Common crimes in Clayton, GA, in comparison to state and national averages
Graph 1. Common crimes in Clayton, GA, in comparison to state and national averages (Georgia Bureau of Investigations, 2016)

Proposal for Training

The successful implementation of intelligence-led policing is impossible without training police officers on the new paradigm in law enforcement. A brief literature research has shown that at present, there are very few studies in police training of any kind. Skogan, Van Graen, and Hennessey (2015) argue that legal theorists and practitioners know virtually nothing about the long-term and short-term impact of police training. The scarcity of evidence on the subject matter was recognized by the US National Research Council that highlighted the importance of comprehensive educational programs for police officers.

The aforementioned facts suggest that the Clayton Police Department will likely have to rely on itself in devising a study program for its employees. By doing that, it will need to avoid the pitfalls of other training programs pointed out by the US National Research Council. Namely, police departments rarely request any feedback or give out questionnaires at the end of training. This leads to breaches in communication and unmet expectations with regards to continuing education.

The training program for the Clayton Police Department needs to be problem-based and practice oriented. It should not ignore the theoretical aspects of intelligence-led policing completely, but at the same time, it is unacceptable to offer police officers a strictly theoretical course. As the model itself suggests, information that does not find practical applications is as good as useless. Makin (2015) describes the implementation of problem-based learning in one of the US police academies and shows that the approach has yielded good results.

According to the researcher, PBL offers a wide set of advantages: it helps students to refocus on core job tasks due to its relevance and improves their critical thinking and problem-solving skills. Besides, PBL keeps students motivated: they engage with each other and the instructor and integrate new material faster.

The training in PBL will include problems for each of the three focal points of the ILP model: criminal environment, data collection and analysis, and decision-making. It is not expected that police officers will learn how to use complex mathematical methods. However, they will have a better understanding of how decisions can be grounded in data. This will help them collaborate with analysts more effectively because they will speak the same language. Lastly, the training needs to be customized to meet the needs of participants and the department.

Equipment and Training Cost Analysis

The major part of the budget for police training will be spent toward invited lecturers. The duration of the training program is still subject to debate. The only realistic expense that can be clarified at this point is couches’ hourly rate. New coaches charge around $100-200 per hour while more experienced, veteran speakers and lecturers can charge as much as $400-600 per hour (Erickson Coaching International, 2015). As for equipment, the Clayton Police Department has enough room for holding lectures and practical sessions. It has computers, overhead projectors, whiteboards, and furniture required for organizing classes.

Proposed Outcome

Proposed outcome of the ILP implementation for Clayton County.
Graph 2. Proposed outcome of the ILP implementation for Clayton County.

As seen from Graph 1, the proposed outcome of ILP implementation encompasses significant decreases in crime rates in two categories. Violent crime includes murder and nonnegligent manslaughter, forcible rape, robbery, and aggravated assault. Property crime includes burglary, larceny-theft, motor vehicle theft, and arson. The first milestone that the Clayton Police Department will attempt to pass is decreasing the rates to match the national average. From there on, the police will be making an effort to decrease them even further.

Implementation Plan

The implementation plan for the chosen strategy can be broken down into the following steps:

  1. Problem clarity and clearly defined goals. Improvement needs to be operationalized in a comprehensive way with quantified desired outcomes. Graph 2 outlines the big goals (a decrease in violent and property crimes); however, it is still advisable to define subgoals as well to keep track of the progress;
  2. Effective strategies. The Clayton Police Department will need to identify the individuals through intelligence gathering, overcome isolation and collaborate with other agencies, and make sure that the targeted individuals cannot do harm to the public anymore. To achieve these goals, the police will need to focus on effective intelligence and transition from traditional methods investigating the situation in a backward manner to ILP that looks into the future (Carter, 2016);
  3. Information sharing. The Clayton Police Department will need to create new communication channels internally with its employees and externally with other agencies and institutions;
  4. Continuous assessment. Since ILP relies largely on data, the police will need to make sure that everything is logged, stored, and monitored.

Pitfalls and Legality Issues

For all its advantages, intelligence-based policing is not devoid of certain faults. First and foremost, it is extremely challenging to keep data collection non-intrusive and decision making ethical. Today, when information security has become a problem as prominent as ever, the last thing a legal institution wants to have is to be accused of violating someone’s privacy. As for the decision-making part, as Dekker (2017) writes, being able to predict crimes is desirable for any police department. However, this ability is a double-edged sword as it may as well lead to unfairly targeting individuals and entire communities and interfering with their lives.

The police may end up acting on racial, ethnic, and gender bias just because those belonging to certain demographic cohorts are more likely to commit crimes or misconduct. Lastly, according to Dekker (2017), blindly trusting technology may be quite dangerous: computers are operated by humans who make routinely make mistakes. The police cannot and should not dismiss force majeure events, for example, natural disasters that can destroy technical equipment or cut off access due to electricity supply breaches. Therefore, police officers need to be prepared and have alternative strategies in case ILP fails or proves impractical.

Benefits Analysis

Despite the risks and pitfalls, the implementation of ILP has the potential to provide many advantages and yield stable positive results. Firstly, if properly introduced, the ILP strategy will help the Clayton Police Department to achieve the aforementioned goals: bringing the crime rate down to match the national average. Secondly, implementation will lead to the creation of a working system of data collection and analysis that can be used for other purposes as well. Moreover, connections with other agencies and institutions can help the Clayton Police Department in its subsequent endeavors. Lastly, training will enhance police officers’ hard and soft skills and make them better specialists. They are likely to improve their transferable skills such as problem-solving and critical thinking and apply them to other areas of expertise.

Conclusion

Law enforcement in the developed countries is currently undergoing a philosophical shift in practice. Intelligence-led policing (ILP) is expected to meet the growing demands of the public due to the complexity of the law enforcement environment after the events of September 2001. ILP is built around risk assessment and risk management: it helps to find patterns in crime data and make predictions. Clayton County, Georgia, is one of the many areas that could benefit from ILP implementation.

The proposed outcomes would include a decrease in two categories of crime: violent and property-related. The training for ILP implementation needs to be tied to real-life issues and include thought-provoking problems. For all the advantages that ILP provides, police officers should take precautions: only employ non-intrusive methods and not blindly trust the technology.

References

Broussard, N. C. (2018). Prior knowledge: Innovations for the Austin Police Department.

Budhram, T. (2015). Intelligence-led policing: A proactive approach to combating corruption. South African Crime Quarterly, 52(1), 49-55.

Carter, J. G. (2016). Institutional pressures and isomorphism: The impact on intelligence-led policing adoption. Police Quarterly, 19(4), 435-460.

Carter, J. G., & Phillips, S. W. (2015). Intelligence-led policing and forces of organisational change in the USA. Policing and Society, 25(4), 333-357.

Dekkers, T. (2017). The troubles of intelligence-led policing.

Erickson Coaching International. (2015). How much does coaching pay? Web.

Georgia Bureau of Investigations. (2016). 2016 crime statistics summary report. Web.

Makin, D. A. (2016). A descriptive analysis of a problem-based learning police academy. Interdisciplinary Journal of Problem-Based Learning, 10(1), 1-16.

Skogan, W. G., Van Craen, M., & Hennessy, C. (2015). Training police for procedural justice. Journal of Experimental Criminology, 11(3), 319-334.

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StudyCorgi. 2021. "Intelligence-Led Policing: A Proactive Approach to Combating Corruption." June 30, 2021. https://studycorgi.com/intelligence-led-policing-a-proactive-approach-to-combating-corruption/.

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