Across differing roles in public safety and emergency services agencies, CFS Analytics™ creates efficiencies, improves operations, and can bolster community relations. Top administrators get big-picture insights into their agency’s performance and resource allocation, optimizing them and operating more efficiently. CFS Analytics™ easily puts KPIs into the hands of staff at all levels, while leaving analysts free to focus on the deeper research and finding important trends.
As a cloud-based application, CFS Analytics™ interfaces with many top nationally-approved CAD vendors, incorporating and processing CFS data (as well as AVL and RMS data) for quick and easy analysis, displayed in a user-friendly dashboard that easily toggles between raw data, charts, and graphs.
Calls are broken down by type, time, and location and then sorted in multiple ways to give greater insight into emerging trends, resource deployment, and response times.
Built on web technologies that run on existing hardware, CFS Analytics™ is quickly deployable across your agency with accessible, near real-time public safety analytics, and readily available at your fingertips.
Backed by RTI International’s team of experts who collaborated with public safety, fire, and EMS agencies to create this web-based application, new research and development will continuously keep CFS Analytics™ updated, timely, and relevant.
CFS Analytics has a robust data architecture that makes CFS data analytically accessible. It is built on web technologies that run on existing hardware, making it quickly deployable across your agency with accessible, near real-time law enforcement analytics. As a cloud-based technology, CFS Analytics easily scales based on the size of your agency.
CFS Analytics helps you visualize the allocation of patrol resources and identify the proportion of patrol resources dedicated to specific activities, such as citizen-initiated calls and self-initiated calls. With the example below, you can easily see where citizen-initiated calls increase through daytime hours while proactive activity remains fairly constant. This can help decision makers determine how many officers are available at any given time to engage in higher levels of proactive activity.
The tool visualizes CFS data in a way that readily identifies patterns and trends for users. The visualization shown below groups calls-for-service by their address to identify high call volume locations. Users can then drill down to specific addresses to see what types of calls are occurring with the greatest frequency. The tool aggregates high call volume locations from the jurisdiction-level down to the block-level, as seen in the example below.
CFS Analytics provides the ability to determine when and where calls are happening. Call volume heatmaps show when calls are taking place as well as call quantity. In this example, you are able to drill down to determine whether quality-of-life calls have a similar temporal pattern. This heatmap shows that downtown quality-of-life calls for service are most commonly occurring between 8 a.m. and 7 p.m., Tuesdays through Saturdays.
This tool helps you to easily determine when and where calls are happening by filtering by district and priority type. This chart shows that District 4 takes the longest time to respond, whereas District 2 is the quickest to respond.
Once you determine where and when calls are happening, you can drill down by priority to determine why District 4 is taking the longest time to respond. This graph shows that Priority 5 calls are occupying more of District 4 officers’ time, while Priority 6 is not occupying much time at all.
You can also review District 4 calls by officer response time and nature to see what types of calls are occupying District 4. As you can see, most calls are hang-up calls. The next two highest categories are sex offenses and all other property calls.