{"id":19925,"date":"2014-04-01T12:00:00","date_gmt":"2014-04-01T16:00:00","guid":{"rendered":"http:\/\/iacpmag.wp.matrixdev.net\/research-in-brief-predictive-policing-understanding-and-applying-analytical-techniques-to-prevent-and-combat-crime\/"},"modified":"2017-01-04T13:29:23","modified_gmt":"2017-01-04T18:29:23","slug":"research-in-brief-predictive-policing-understanding-and-applying-analytical-techniques-to-prevent-and-combat-crime","status":"publish","type":"post","link":"https:\/\/www.policechiefmagazine.org\/research-in-brief-predictive-policing-understanding-and-applying-analytical-techniques-to-prevent-and-combat-crime\/","title":{"rendered":"Research in Brief: Predictive Policing: Understanding and Applying Analytical Techniques to Prevent and Combat Crime"},"content":{"rendered":"<p>While predictive policing has seen widespread use in recent years, the field has lacked a comprehensive resource that assesses the most commonly used tools and helps departments determine which are most appropriate for their jurisdiction. In 2013, Rand Corporation published such a resource: <i>Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations<\/i>. This National Institute of Justice (NIJ)-funded research assesses various models of predictive policing, examines promising approaches for acting on predictions, and dispels common myths associated with predictive policing.<\/p>\n<p>The researchers conducted a literature review including academic papers, vendor presentations, and lessons learned from similar predictive techniques in use at the U.S. Department of Defense. They also reviewed a variety of departments using promising predictive techniques. Researchers then synthesized this information into a taxonomy of the various operational applications that predictive policing can support.<\/p>\n<p><big><b>The Results<\/b><\/big><\/p>\n<p>Researchers found that predictive methods generally fall into one of four categories:<\/p>\n<ol>\n<li>Crime predictors. These methods rely on mapping crime locations and identifying hot spots. Analytics then range from regression analysis to cutting-edge mathematical models.<\/li>\n<li>Offender predictors. These methods, aimed at identifying individuals at high risk to commit a crime, generally rely on clinical techniques to determine risk. The corresponding analytics then use regression and classification models to associate risk factors with the percent chance the person will offend.<\/li>\n<li>Perpetrator identity predictors. These methods help solve crimes that have occurred. Investigators link suspects to crimes using available crime scene information and a process of elimination. Analytics automate the process, allowing for the linkages to happen across large data sets.<\/li>\n<li>Crime victim predictors. These methods often blend those used to predict crime location and offender risk.<a href=\"#1\"><sup>1<\/sup><\/a><\/li>\n<\/ol>\n<p>Researchers also found that predictive policing is \u201cbest thought of as part of a comprehensive business process.\u201d In other words, while predictive policing is informative, interventions actually lead to crime reduction. Researchers identified a four-step cycle for conducting this process.<a href=\"#2\"><sup>2<\/sup><\/a><\/p>\n<ol>\n<li><i>Data collection<\/i>. Crime, incident, and offender data are collected and will be used to inform predictions. Data from different community resources may require some synthesis prior to analysis.<\/li>\n<li><i>Data analysis<\/i>. Analysis of this data using an appropriate predictive method and tool.<\/li>\n<li><i>Police operations<\/i>. Operations will vary depending on the intervention necessary as informed by predictive analytics. They range from generic (an increase of resources in a high risk area), crime-specific (a targeted intervention), or problem-specific (addressing both locations and factors driving risk).<\/li>\n<li><i>Criminal response<\/i>. Ideally, crimes are reduced or solved. Here, agency assessments are key to ensure interventions are implemented properly.<\/li>\n<\/ol>\n<p><big><b>Predictive Policing Myths<a href=\"#3\"><sup>3<\/sup><\/a><\/b><\/big><\/p>\n<ol>\n<li><i>The computer knows the future<\/i>. It is important to remember that the algorithms used in predictive policing predict the risk of future events, not the occurrence of the events themselves. It is also important to remember that these predictions are based on data from past events; the better the data, the better the predictions.<\/li>\n<li><i>The computer will do everything for you<\/i>. The human element in predictive policing is in fact the most essential. Even with the most advanced, comprehensive predictive policing software, people must collect and process the data for analysis, design the analysis so that it is responsive to evolving conditions in their jurisdictions, and be cognizant of<br \/>\nerroneous findings, among others.<\/li>\n<li><i> Each department needs a high-powered, costly model<\/i>. The functionalities of most standard workplace software like Microsoft Office and the capabilities of such standard geographic information systems like ArcGIS are suitable for use with many predictive policing models. And while a more complex model generally does yield greater predictive power, the benefits diminish as the model complexity increases.<\/li>\n<li><i>Accurate predictions equal major decreases in crime<\/i>. It is important to remember that predictions are nothing without subsequent action. Using predictions to inform patrols and assignment of officers is essential for a jurisdiction to experience a crime decrease.<\/li>\n<\/ol>\n<p><big><b>Recommendations<\/b><\/big><\/p>\n<p>Predictive policing methods and tools can be beneficial to agencies of all sizes in all regions regardless of proximity to urban areas. The question that remains for a law enforcement agency is determining the complexity (and related expense) of the model necessary to achieve the desired impact.<\/p>\n<p>Small agencies with low crime rates and routine crime distribution will likely need only basic statistical and display capabilities; these are often available for free and interface with existing software such as Microsoft Office, basic geographic information tools, and statistics packages. Some also interface with advanced visualization tools such as CrimeStat, an NIJ-sponsored spatial statistics program for the analysis of crime incident locations available to law enforcement agencies for free.<a href=\"#4\"><sup>4<\/sup><\/a><\/p>\n<p>Large agencies that have considerable incident and intelligence data for analysis would benefit from more complex and sophisticated predictive policing tools. Not only will these systems assist agencies in determining the when, where, and who of criminal incidents, they will also help agencies understand the underlying factors that drive crime in their jurisdictions. There are many things to consider before investing in what will likely be a costly system, some of which include interoperability, ability to incorporate information officers learn in the field, and the conditions under which the system can support analysis, among others.<\/p>\n<p><big><b>Action Items<\/b><\/big><\/p>\n<p>1. Ensure you have the correct data and that it is complete and of the highest quality.<br \/>\n2. Choose the best predictive model and intervention techniques to fit your needs and circumstances.<br \/>\n3. Reference the full report for a complete list of considerations at <a href=\"http:\/\/www.rand.org\/pubs\/research_reports\/RR233.html\">http:\/\/www.rand.org\/pubs\/research_reports\/RR233.html<\/a>.\u2666<\/p>\n<p><b>Notes:<\/b><br \/>\n<a name=\"1\"><\/a><sup>1<\/sup>Walter L. Perry et al., <i>Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations<\/i> (Santa Monica, CA: RAND Corporation, 2013), xiv.<br \/>\n<a name=\"2\"><\/a><sup>2<\/sup>Ibid., xvii\u2013xviii.<br \/>\n<a name=\"3\"><\/a><sup>3<\/sup>Ibid., xix\u2013xx.<br \/>\n<a name=\"4\"><\/a><sup>4<\/sup>For more information about CrimeStat, please visit <a href=\"http:\/\/www.nij.gov\/topics\/technology\/maps\/Pages\/crimestat.aspx\">http:\/\/www.nij.gov\/topics\/technology\/maps\/Pages\/crimestat.aspx<\/a>.<\/p>\n<p>Please cite as:<\/p>\n<p style=\"margin-left: .5in;\">William Ford, \u201cPredictive Policing: Understanding and Applying Analytical Techniques to Prevent and Combat Crime,\u201d <i>The Police Chief<\/i> 81 (April 2014): 12\u201313.<\/p>\n<p align=\"center\">\n","protected":false},"excerpt":{"rendered":"<p>While predictive policing has seen widespread use in recent years, the field has lacked a comprehensive resource that assesses the most commonly used tools and helps departments determine which are most appropriate for their jurisdiction. In 2013, Rand Corporation published such a resource: <i>Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations<\/i>. This National Institute of Justice (NIJ)-funded research assesses various models of predictive policing, examines promising approaches for acting on predictions, and dispels common myths associated with predictive policing.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[152,160],"tags":[],"class_list":["post-19925","post","type-post","status-publish","format-standard","hentry","category-columns","category-research-in-brief"],"acf":{"post_author":"<strong>William Ford, Division Director, Office of Science and Technology, National Institute of Justice<\/strong>","legacy_article_id":"3322","legacy_issue_id":"42014","main_category":"Research in Brief"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.4 (Yoast SEO v24.4) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Research in Brief: Predictive Policing: Understanding and Applying Analytical Techniques to Prevent and Combat Crime - Police Chief Magazine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.policechiefmagazine.org\/research-in-brief-predictive-policing-understanding-and-applying-analytical-techniques-to-prevent-and-combat-crime\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Research in Brief: Predictive Policing: Understanding and Applying Analytical Techniques to Prevent and Combat Crime\" \/>\n<meta property=\"og:description\" content=\"While predictive policing has seen widespread use in recent years, the field has lacked a comprehensive resource that assesses the most commonly used tools and helps departments determine which are most appropriate for their jurisdiction. 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