We live in the world of Big Data. Organizations of all types are generating, managing and analyzing large amounts of data to inform their decision making. Law enforcement agencies are no different. They too are generating data as a function of the work that officers do in the community. Calls-for-service data is an information-rich dataset that documents interactions between police and the community and include both interactions initiated by citizens and by officers. This information includes the number and types of calls for service received, the type and efficiency of the response, when and where officers are deployed, and the outcome of the officer and citizen interactions. Leveraging calls-for-service data is essential to law enforcement agencies dedicated to data-driven operations.
However, analysis of calls-for-service data can be challenging. Some of these challenges include the volume and complexity of the data as well as the lack of effective tools to allow for meaningful insights. Many law enforcement agencies may feel overwhelmed by the task of operational analysis; they have all the data but no way to leverage it. CFS Analytics mitigates these challenges and allows law enforcement agencies to make informed decisions about critical operational questions.
By analyzing calls-for-service data and other related information, law enforcement can better manage officer performance and workload across units within their agency. For example, throughout a 24-hour, 7-day, or 28-day period, the proportion of officer time spent on citizen calls or police-initiated activity, such as directed patrol in specific areas, can vary. This type of information, along with the number of officers available at any given time, can help agencies create a dynamic process for comparing resource needs versus staff capacity. Further, agency leaders can proactively identify opportunities to support agency priorities such as community-based and place-based policing.
Another topic of interest, inside and outside law enforcement agencies, is efficient responses to citizen calls-for-service. However, many agencies do not have the ability to routinely calculate and compare response times with a high level of specificity, including by call type, priority, location, and day of week. CFS Analytics allows users to get past superficial response time analysis and develop a deeper understanding of their agency’s responses. For example, agency decision makers may quickly compare response times across squads while controlling for things like call volume and level of staffing.
Finally, CFS Analytics can be used to develop internal benchmarks. Establishing relevant benchmarks allows agencies to set performance “triggers”; this enables decision makers to become aware of situations as they are developing rather than after the fact. There are many opportunities for operational benchmarking. Find answers to questions like: Are the agency’s patrol officers routinely engaging in proactive policing at the intended time and place? Have calls for specific types of calls increased significantly in particular neighborhoods, suggesting that some neighborhood dynamics are changing? Are there certain types of calls in which officers are spending a disproportionate time to address? Do officers have the necessary time to handle more complex calls such as domestic violence incidents?