Statistical Data Usage in Criminal Justice Leadership

When leaders in the field of criminal justice are going to develop, change or implement policies within their field, it is always important that these developments, changes and implementations are grounded in evidence. Evidence-based practice is universally recognized as essential to good decision making (Noe, Hollenbeck, Gerhart & Wright, 2003). In order to use the evidence, one has to obtain the evidence—and that happens by way of statistical analysis and research.

Researchers who gather, assess and use statistical data to understand an issue and devise a solution to a problem are grounding their work in evidence that can be quantified. When evidence can be quantified—i.e., statistically measured—it is easier to see when policies are working and when they are not. For example, in criminal justice policy making, leaders might want to institute a new way method for police to report internally on abuses in the workplace.

The method they choose, however, may have been shown to be ineffective through statistical analysis by a number of studies conducted by researchers in the criminal justice field. If the leaders see this or have access to the data, they can re-think their desire to implement such an ineffective policy and save their department a great deal of headache and cost by going back to the drawing board and developing or implementing a policy that will work, according to the statistical data available.

This paper will show why using statistical data is so important and critical for criminal justice leadership: without it, leaders are essentially making decisions without evidence based on quantifiably measured information—i.e., they are flying blindly. Statistical data helps leaders to understand in clear, precise and concise numbers exactly to what degree a strategy or policy is effective. Statistics have a way of simplifying how people understand a problem or a phenomenon.

They also are the result of procedures that can be re-tested and verified, so there is less risk that a researcher is simply making up results in order to produce an outcome that is desired by this or that stakeholder. Such is the problem with qualitative studies: the research methods involved in qualitative analysis can be less rigorous and informative for researchers and professionals than quantitative analysis. Yet some leaders will prefer basing their policies on qualitative literature because it is thematic, conceptual and oftentimes more emotionally appealing.

Quantitative studies, however, appeal to the logical side of the mind, the empirical aspect of research, which requires physical evidence that can be seen and duplicated in a second and third study so that results and statistics are verified. Statistical data can be tested and proved accurate in ways that qualitative data simply cannot be. For criminal justice policy making, statistical support can come in a number of ways.

For example, as Sibley (2015) points out, statistical data is a great way to create a database of information that can be used to shape the way leaders in criminal justice go about making decisions regarding policy. The better the database, the more information they have to draw upon, and the better informed those decisions will be. Sibley (2015) notes that “the most well-known criminal justice data set is the Uniform Crime Report (UCR), collected by the FBI since 1930.

The UCR includes statistics on seven crimes classified as either violent crime or property crime: murder, rape, assault and robbery fall under the violent crimes category, while arson, burglary, larceny-theft and motor vehicle theft fall under property crimes.” A database like the one maintained by the FBI is highly useful in supplying data and information that can be used to create policies in criminal justice as it basically serves as a giant store of what issues are spreading, where problem areas can be found, and what percentages of crimes involve specific types of behavior and where they are occurring.

Statistical data helps leaders to see patterns over time and to base decision making when creating policies on the patterns that emerge. An alternative to the UCR is the National Incident Based Reporting System (NIBRS), which also supports policy making. As Sibley (2015) shows: · Using the NIBRS, legislators, municipal planners/administrators, academicians, sociologists, and the public will have access to more comprehensive crime information than the traditional summary reporting system can provide.? · NIBRS produces more detailed, accurate, and meaningful data than the summary reporting system.

Armed with such information, law enforcement can better make a case to acquire the resources needed to fight crime.? · NIBRS enables agencies to find similarities in crime-fighting problems so that agencies can work together to develop solutions or discover strategies for addressing the issues (Sibley, 2015). Using the kind of statistical data obtained from such an instruments makes leaders more informed and more effective in setting a variety of policies. Statistical data usage can also be helpful in producing criminal justice research in support of community policing.

For example, researchers may be able to show statistically how community policing leads to a decrease in violent crime in a community, or how it is connected to an increase in favorable reports from the community to the police department. Researchers can use statistics to show that community policing helps to reduce the rate of reports of domestic violence, drug usage, and vandalism in a community. Such research can also be used to help support this type of policing in other areas where less effective styles of policing are used.

Statistical data can be more persuasive than any other kind. Criminal justice researchers can also use statistical data in support of community engagement. For example, researchers can measure the number of people who show up for civic activities, the number of people who come to community meetings, the increase or decrease in positive correspondence and communications between officers, administrators and members of the community, and so on. Statistical.