Maximizing Public Safety Data for Intelligence-Led Policing

For the past several years, there has been a growing emphasis on analytics and “big data” in the business world, and despite lagging behind that trend, the public safety industry now seems positioned and interested in implementing those same principles. While the idea of law enforcement decision-making that is based on the mathematical, scientific approach of gathering and using data to help efficiently and effectively allocate resources isn’t new (think CompStat), there have been impressive technological advancements with Intelligence-Led Policing (ILP).


The hope is that with the right analytics tools, a law enforcement agency can anticipate, and in some cases predict, where and how crime will occur. Because of the advancements in ILP, many agencies are looking for the ability to analyze data by crime-specific categories with the ability to analyze multiple data layers on a jurisdictional map, filter searches by time and date, and even compare time periods on the map to discover crime trends. Positive results of an effective Intelligence-Led Policing strategy include lower crime rates, more arrests, and a safer community. With this in mind, one of the most efficient ways to advance Intelligence-Led Policing is adopting an analytics program that will integrate with and leverage the data that agencies have been collecting for years.

A great example of an agency successfully using data for ILP is the Riley County Police Department (RCPD) in Manhattan, Kansas. The RCPD recently earned the Bronze IACP/Sprint Excellence in Law Enforcement Research Award for the agency’s work on hotspot policing with BAIR Analytics to use past data for “Initiative: Laser Point,” an ILP project with Kansas State University. With this initiative, the agency analyzed map-viewable data to pinpoint geographical areas that had high crime activity. According to the award announcement in The Police Chief magazine, RCPD’s work in hotspot policing successfully “decreased calls for services and Part I/Part II crimes when comparing the same geographic areas over a four-year period.”

It is becoming more and more apparent that ILP is not a passing trend, and many agencies are looking forward to adopting ILP initiatives. It is imperative that agencies identify how their analytics software will integrate into their existing processes. While a robust, map-based analytics package will offer any agency increased awareness and improved decision-making, if that analytics software runs alongside – rather than within – the agency’s existing database, the result will require the duplicate entry of data, which becomes a burden to an agency’s workflow.


Like RCPD, Spillman has recognized the public safety benefit of providing detailed, map-level data and has partnered with industry-leading BAIR Analytics to develop Spillman Analytics®, a fully integrated analytics module. recently recognized Spillman Analytics in its Hot Products for 2014. Because Spillman Analytics is designed to work inside the Spillman system, with one single point of access, it is fully integrated with all other Spillman modules and offers personnel streamlined access to complete incident records directly from the analytics level and can be used to analyze data entered throughout daily operations. Spillman Analytics’ intelligence tools can help agencies use their existing data to make informed daily operational decisions, enable more effective day-to-day policing, and enhance investigative insights without having to enter data into and use multiple systems.

With this addition to Spillman’s ILP offerings, agencies have the opportunity to analyze crime trends and implement intelligence-led policing initiatives. Leveraging the true integration to the Spillman system allows personnel to take advantage of the “Big Data” trend by using the data they are already collecting.