{"id":22324,"date":"2016-09-28T18:36:36","date_gmt":"2016-09-28T22:36:36","guid":{"rendered":"http:\/\/iacpmag.wp.matrixdev.net\/?p=22324"},"modified":"2024-10-07T12:14:15","modified_gmt":"2024-10-07T16:14:15","slug":"overcoming-law-enforcement-data-obstacles","status":"publish","type":"post","link":"https:\/\/www.policechiefmagazine.org\/overcoming-law-enforcement-data-obstacles\/","title":{"rendered":"Overcoming Law Enforcement Data Obstacles"},"content":{"rendered":"<p>RMS (records management system) and CAD (computer-aided dispatch) are acronyms that every police officer has probably heard at least once in his or her career. Similarly, predictive policing, intelligence-led policing, and problem-oriented policing are concepts that law enforcement agencies around the world use on a daily basis to engage their citizens and combat crime. The acronyms and concepts may seem like standalone cogs in the policing machine at first glance, but they are forever linked by a myriad of data pieces that must be obtained, integrated, and acted upon. The problem lies in getting the pieces to interconnect with and communicate accurate information to other technology items.<\/p>\n<p>Data, in and of themselves, are not bad. Police departments have always collected data in some fashion. Data collection started with pen and paper, evolved into communication over the telephone or radio, and finally moved into varying digital iterations. The ever-growing need for more and better shared data has consumed all departments, large and small. The drive to implement emerging technologies into police departments is in full force. Citizens want to be able to view crime statistics from their local departments\u2019 webpages, submit a police report over the Internet, and download digital copies of their accident reports, all from the comfort of their living rooms. The age of carbon copy or handwritten police reports is a distant memory (or unheard of) for most law enforcement personnel.<\/p>\n<p>The way that a law enforcement agency deals with data can either be a headache or serve as a force multiplier to increase efficiency and citizen interaction. For most police administrators, it is probably a little of both. The challenge is that data can become overwhelming\u2014and can also be a little intimidating\u2014but correct data are the most important foundational cornerstones that must be laid before any new technology can be properly utilized. A carefully considered data philosophy and proper planning can help an agency minimize data obstacles.<\/p>\n<h3 class=\"ARTICLE-SUBHEAD-2014\"><span class=\"CharOverride-106\" style=\"color: #ff0000;\">Departmental Data Philosophy<\/span><\/h3>\n<p class=\"ARTICLE-TEXT-2014\">Once new police chiefs accept their congratulations and settle in, they get a chance to look around the agency they now lead. Most of the time, they will notice that a firm foundation has already been established. RMS system, check. CAD system, check. Laptop computers in the patrol vehicles, check. What these leaders quickly realize is that they have a plethora of data at their fingertips. A 2001 study showed that law enforcement agencies are becoming more reliant on digital data as computer technology becomes more readily available.<span class=\"CharOverride-35\"><sup>1<\/sup><\/span> This trend does not look to be slowing down anytime soon with advances in portability, such as the creation of the smartphone, and overall decreases in technology prices. The infrastructure to receive digital data is clearly in place in many agencies, but the underlying data may not be ready to feed into that infrastructure. Police departments have to have an idea of the end product in order to align the data properly.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">End product design depends largely on understanding the consumer. In the United States alone, millennials now number 83 million persons and make up a quarter of the total population.<span class=\"CharOverride-35\"><sup>2<\/sup><\/span> The youngest individuals in this age group are around 17 years old, while the oldest are around 34, depending on the definition of \u201cmillennial\u201d used. This age group is interacting with data every day. In fact, one of the specific attributes of the group is that the members grew up with the Internet and social media easily available. In other words, they expect all data\u2014including law enforcement\u2013related data\u2014to be delivered in an instant, convenient, electronic format. Think back to the days when citizens had to drive downtown; park their car; walk inside police headquarters; find the Records section; wait in line; and, finally, get a copy of their incident report. If an agency makes a millennial go through this process today, he or she will be less than pleased.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">Citizens are not the only consumer group to consider. Police administrators must also design end products geared toward employees. As time goes by, increasing numbers of millennials will join law enforcement agencies, and they will expect to engage emerging technologies in a way that they are accustomed to. Terminal access and handwriting may not be their first choice for data collection methods. An administrator\u2019s philosophy on data collection and end product technology design has a hefty influence on operations.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">The philosophies surrounding data use can help mitigate some of the trouble with data. Administrators have to understand that the policies guiding overall data use and, specifically, the exact way in which data are actually utilized have a direct effect on desired outcomes.<span class=\"CharOverride-35\"><sup>3<\/sup><\/span> Data philosophies help shape perspective. Think back to the scenario involving millennials and police reports. One possible reaction is that of perceived opportunity. Perhaps the hypothetical administrator of this law enforcement agency could streamline the process and deliver the data in a different format that would save time and effort. However, another reaction might be a feeling that the police administrator should change nothing and millennials should just accept the process as it stands.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">There is nothing wrong with either of those stances. Police departments come in different shapes and sizes with different budgets and communities. Each police administrator must have the discretion to push the agency in a direction that best suits the organization\u2019s unique set of requirements. However, caution must be urged when dealing with leadership discretion. Historically, police departments have proven better at altering the outward appearance of change rather than engaging in meaningful internal reform.<span class=\"CharOverride-35\"><sup>4<\/sup><\/span> This thought process is applicable to data. A data-sharing philosophy that centers on placating the masses will not do much to enhance departmental performance. An example of this may be an agency that puts \u201ccommunity policing\u201d or \u201cevidenced-based policing\u201d on all their community handouts, yet does not use data in a meaningful way to support those strategies.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">Police administrator philosophies guide every aspect of a law enforcement agency. Take the popular \u201copen door\u201d philosophy, for example. Some chiefs believe that officers should go through the chain-of-command in every instance and that no line-level officer should walk through the chief\u2019s doors uninvited. Some chiefs believe that everyone in the department should be able to meet with whomever without fear. Those very different philosophies will dramatically alter the mechanics and operations of a law enforcement agency. In much the same way, a chief\u2019s philosophy on data use will have a reverberating effect within a department. Aligning a data philosophy with desired outcomes and end users is a necessity.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">There are three steps to aligning a data philosophy with desired results. The first step in the process is to understand what the underlying policing strategy is going to be. Will the strategy involve a focus on strict, reactionary principles where police officers primarily respond to calls? In this case, a strong RMS and CAD system may be the focus of data needs. If the strategy consists of community policing principles, such as active engagement and information sharing, then RMS and CAD data are the tip of the proverbial data iceberg.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">Simply looking at high crime rates in a geographical area (gathered from mapped RMS data) is not enough under the community policing model. Rather, properly identifying the underlying contributors to the crimes is key to stopping them.<span class=\"CharOverride-35\"><sup>5<\/sup><\/span> Those underlying contributors are separate data points that must be collected and analyzed. This expanded data set could include the addresses of sex offenders, recently released parolees, or liquor stores. Perhaps the expanded data set would include an enhanced intelligence or information repository component. Items such as intelligence databases can be an intimidating thought for some administrators, but these types of data could prove irreplaceable when addressing the needs of the community.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">The second step in the alignment process is to understand the organization\u2019s culture. Some police administrators will have no problem in integrating data throughout the daily police workflows. In contrast, some police administrators will experience quite a bit of pushback if they were to fully integrate data, especially data that fall under a new collection model or relate to information that was not previously disseminated. The psychological contract aspect of police administrator and police employee relationships must be maintained in order to develop trust and understanding.<span class=\"CharOverride-35\"><sup>6<\/sup><\/span> Employees must trust that their leaders have their best interests at heart. Within the context of changing an organizational culture\u2019s view on data gathering and use, the trust between leadership and line-level officers requires a strong foundation. A large part of that strength comes from the communication between the different organizational levels.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">The third step in the alignment process is the prioritization of communication. From a leadership perspective, the need to increase data collection and analysis might seem obvious as a department modernizes and meets new mandates. From the perspective of line-level officers, though, the changes can look more akin to increased workload and increased responsibilities with little payoff. An organization that ignores communication feedback loops while focusing primarily on goals is more prone to unintended consequences.<span class=\"CharOverride-35\"><sup>7<\/sup><\/span> These unintended consequences could come in many forms, such as decreased trust, decreased efficiency, and disgruntled employees. The transition from data philosophy to intended results might not be an easy one, but it can be made easier if the vision is communicated in a meaningful way to everyone involved.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">Following these three steps will allow a law enforcement organization to align its data philosophy with its desired outcomes. Before proceeding down the path of achieving those outcomes, administrators must also properly plan for their data journey. The proper use of data is not a work process that can just occur naturally overnight. There are items to be considered and goals that must be established. Planning is paramount.<\/p>\n<h3 class=\"ARTICLE-SUBHEAD-2014\"><span class=\"CharOverride-106\" style=\"color: #ff0000;\">Planning<\/span><\/h3>\n<p class=\"ARTICLE-TEXT-2014\">Knowing an end point or goal is important, but understanding how to get there is just as important, if not more so. Aligning a data philosophy with outcomes points the way, serving as a compass in the process, and proper planning is the map to those expectations. Planning is important in every aspect of an organization, but it is even more important when it comes to data integration and use. One trouble with data collection and use is that it is not an instantaneous process, but rather an arduous journey that takes time. To one day decide that data need to be used in a meaningful way and then expect to have a fully functioning system up and running the next day is short-sighted. Fortunately, or unfortunately, there are a myriad of hardware and software vendors out there that recognize that many law enforcement agencies struggle with data planning and would be happy to assist them on their data journey.<\/p>\n<div id=\"_idContainer721\" class=\"Basic-Text-Frame\">\n<blockquote>\n<p class=\"PULL-QUOTE-FILLER\"><span class=\"CharOverride-106\"><span style=\"color: #ff0000;\">Knowing an end point or goal is important, but understanding how to get there is just as important, if not more so. Aligning a data philosophy with outcomes points the way, serving as a compass in the process, and proper planning is the map to those expectations.<\/span><\/span><\/p>\n<\/blockquote>\n<\/div>\n<div class=\"_idGenObjectLayout-1\">\n<div id=\"_idContainer722\" class=\"Basic-Graphics-Frame _idGenObjectStyleOverride-4\"><\/div>\n<\/div>\n<p class=\"ARTICLE-TEXT-2014\">The number of law enforcement agencies that have been sold on a very expensive piece of software, only to find that it does not spin hay into gold, are probably too numerous to count. This is not entirely the fault of the software vendors\u2014many times the software does exactly what it was designed to do, but departments have inadequately planned for how the software will be integrated going forward or how it will be expanded into future operations. Strategic planning can help facilitate some of the discussions around data integration. While strategic planning is not a commonplace process in some law enforcement agencies, there have been a number of successes in agencies that integrate as many internal personnel as possible during the early stages of planning.<span class=\"CharOverride-35\"><sup>8<\/sup><\/span> This allows for good communication and a sense of buy-in and minimizes unintended consequences.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">In addition to strategic planning, there are other ways to properly plan for data integration. One way to increase the potential for success is to keep an open mind on what the data can do for the organization. It is very easy for administrators to focus on solving only one problem. For instance, simply getting a count on the number of traffic stops that occur in a month can be accomplished fairly easily with a two-column form. However, leaders need to look beyond that simplistic data picture. What is the goal of a traffic stop? Is it to deter crime? If so, then maybe the traffic stops need to be plotted geographically so that they can be assessed for proximity to crime hotspots. This is an over-simplified example, but imagine if a contractor was hired to create that initial two-column form because all that was initially needed was a count. A simple count can be great, but planning would have allowed the data to better align with broader goals and aid in explaining the multifaceted value of a traffic stop more vividly, providing a value metric instead of just a simple measurement. The value measure can then be used to show the benefit the department provides rather than just the workload it performs.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">Using an outside vendor may be the simplest, quickest way to set up a data system. This process can lead to other troubles though. When using a vendor, it is very important to be mindful of siloed data. In many cases, outside vendors set up proprietary databases and algorithms that may or may not interface with other data systems easily. In some cases, pre-existing databases or future databases can be integrated, but the integrations may have a high cost, in the form of manpower and fees, attached to them. For some police departments, cost is not a problem, but for many departments, it is an important issue. When databases are not integrated, the phenomenon of siloed data takes place. The term siloed data refers to a group of standalone data pieces that have minimal integration and line-of-sight. This situation is problematic; it is quite possible that there are pertinent data across multiple databases that could add to the totality of circumstances in any given case. There is no greater example of this than that of 9\/11. Siloed data and the lack of integration and communication had a negative impact on the possibility of preventing the incident.<span class=\"CharOverride-35\"><sup>9<\/sup><\/span> Having sight of all the puzzle pieces allows for a better understanding of the complete picture. For this reason, siloed data should be avoided through proper planning.<\/p>\n<p class=\"ARTICLE-TEXT-2014\">One way to overcome siloed data is to build an in-house solution. There are some very innovative and intuitive RMS out there that were built entirely from within the ranks of in-house staff. The Lincoln, Nebraska, Police Department is a great example of this. Their RMS was built by a team of police officers who were tasked with creating a solution that best fitted the needs of their department. Twenty years later, a robust and fully integrated RMS is proof that in-house solutions can work, as evidenced by the attention it has garnered from outside entities.<span class=\"CharOverride-35\"><sup>10<\/sup><\/span><\/p>\n<p class=\"ARTICLE-TEXT-2014\">An in-house solution has obvious benefits. The system can be modified by an internal employee that is already on payroll and does not require a \u201cnominal fee\u201d for modifications by outside parties. The system can be upgraded as new data components enter the workflow and can expand and contract with workload variabilities. Finally, it can be tailored to the needs of a specific organization. Off-the-shelf RMS solutions try to be \u201cone-size-fits-all\u201d software, but they cannot be everything to everyone. It may seem like a headache to hire and retain a gifted individual to build and run the agency\u2019s data systems, such as an RMS, but doing so can pay great dividends down the road. In the end, organization leaders need to be planning for the future, not just the present.<\/p>\n<h3 class=\"ARTICLE-SUBHEAD-2014\"><span class=\"CharOverride-106\" style=\"color: #ff0000;\">Conclusion<\/span><\/h3>\n<p class=\"ARTICLE-TEXT-2014\">Data collection and analysis can seem intimidating to some people, but these decision-enhancing techniques are merely tools that can be used to great effect under the right set of circumstances. The first part of properly leveraging data is to align the department\u2019s data philosophy with expected outcomes. This is accomplished by understanding the foundational policing strategy, understanding the departmental culture, and prioritizing communication. After setting the direction of where a department wants to go, the next step is to plan out how to get there. Proper planning involves such aspects as strategic planning techniques, but also can be aided by keeping an open mind as to what the data can provide, avoiding siloed data solutions, and exploring the possibilities of in-house solutions. In the end, data use should not be viewed as an obstacle, but rather as an opportunity for the enhancement of overall public safety. <span class=\"CharOverride-16\">v<\/span><\/p>\n<h4><span class=\"PALATINO-NOVA-PRO-BOLD\">Notes:<\/span><\/h4>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>1<\/sup><\/span>Samuel Nunn, \u201cPolice Technology in Cities: Changes and Challenges,\u201d <em><span class=\"PALATINO-NOVA-PRO-ITAL\">Technology in Society<\/span><\/em> 23 (2001): 11\u201327.<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>2<\/sup><\/span>U.S. Census Bureau, <em><span class=\"PALATINO-NOVA-PRO-ITAL\">Millennials Outnumber Baby Boomers and Are Far More Diverse<\/span><\/em> (Washington, D.C.: Office of Census Bureau Reports, 2015), <a href=\"https:\/\/www.census.gov\/en.html\">https:\/\/www.census.gov\/newsroom\/press-releases\/2015\/cb15-113.html<\/a> (accessed May 3, 2016).<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>3<\/sup><\/span>Mary A. Wolf, Rachel Jones, Sara Hall, and Bob Wise, <em><span class=\"PALATINO-NOVA-PRO-ITAL\">Capacity Enablers and Barriers for Learning Analytics: Implications for Policy and Practice<\/span><\/em> (Alliance for Excellent Education, 2014), <a href=\"http:\/\/all4ed.org\/wp-content\/uploads\/2014\/06\/LearningAnalytics.pdf\">http:\/\/all4ed.org\/wp-content\/uploads\/2014\/06\/LearningAnalytics.pdf<\/a> (accessed May 13, 2016).<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>4<\/sup><\/span>Peter K. Manning,<em> <span class=\"PALATINO-NOVA-PRO-ITAL\">Policing Contingenci<\/span>e<span class=\"PALATINO-NOVA-PRO-ITAL\">s<\/span><\/em> (Chicago, IL: University of Chicago Press, 2010).<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>5<\/sup><\/span>Anthony A. Braga, \u201cBetter Policing Can Improve Legitimacy and Reduce Mass Incarceration,\u201d <em><span class=\"PALATINO-NOVA-PRO-ITAL\">Harvard Law Review<\/span><\/em> 129, no. 5 (March 2016): 233\u2013241.<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>6<\/sup><\/span>Vernon White and Susan Robinson, \u201cLeading Change in Policing: Police Culture and the Psychological Contract,\u201d <span class=\"PALATINO-NOVA-PRO-ITAL\"><em>Police Journal: Theory Practice, and Principles<\/em><\/span> 87, no. 4 (December 2014): 258\u2013269.<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>7<\/sup><\/span>Jake Chapman, \u201cUnintended Consequences,\u201d <em><span class=\"PALATINO-NOVA-PRO-ITAL\">Nursing Management <\/span><\/em>12, no. 4 (July 2005): 30\u201334.<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>8<\/sup><\/span>Keith L. Williams, \u201cBeyond the Rhetoric: Factors Influencing the Implementation of Strategic Plans by American Police Agencies\u201d (PhD diss., American University, 2015).<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>9<\/sup><\/span>Chris Stakutis and John Webster,<em> <span class=\"PALATINO-NOVA-PRO-ITAL\">Inescapable Data: Harnessing the Power of Convergence <\/span><\/em>(Indianapolis, IN: IBM Press, 2005).<\/p>\n<p class=\"ARTICLE-FOOTNOTE-2014\"><span class=\"CharOverride-35\"><sup>10<\/sup><\/span>Pamela Mills-Senn, \u201cSharing the Data: Records Management and Data Sharing Goes Electronic,\u201d<em> <span class=\"PALATINO-NOVA-PRO-ITAL\">Law Enforcement Technology<\/span><\/em> 34, no. 10 (October 2007): 48\u201350.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>RMS (records management system) and CAD (computer-aided dispatch) are ac-ronyms that every police officer has probably heard at least once in his or her career. Similarly, predictive policing, intelligence-led policing, and problem-oriented policing are concepts that law enforcement agencies around the world use on a daily basis to engage their citizens and combat crime. The acronyms and concepts may seem like standalone cogs in the policing machine at first glance, but they are forever linked by a myriad of data pieces that must be obtained, integrated, and acted upon. The problem lies in getting the pieces to interconnect with and communicate accurate information to other technology items.<\/p>\n<p>Data, in and of themselves, are not bad. Police departments have always collected data in some fashion. Data collection started with pen and paper, evolved into communication over the telephone or radio, and finally moved into varying digital iterations. The ever-growing need for more and better shared data has consumed all departments, large and small. The drive to implement emerging technologies into police departments is in full force. Citizens want to be able to view crime statistics from their local departments\u2019 webpages, submit a police report over the Internet, and download digital copies of their accident reports, all from the comfort of their living rooms. The age of carbon copy or handwritten police reports is a distant memory (or unheard of) for most law enforcement personnel.<br \/>\nThe way that a law enforcement agency deals with data can either be a headache or serve as a force multiplier to increase efficiency and citizen interaction. For most police administrators, it is probably a little of both. The challenge is that data can become overwhelming\u2014and can also be a little intimidating\u2014but correct data are the most important foundational cornerstones that must be laid before any new technology can be properly utilized. A carefully considered data philosophy and proper planning can help an agency minimize data obstacles.<\/p>\n","protected":false},"author":3,"featured_media":22423,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[146],"tags":[],"class_list":["post-22324","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"acf":{"post_author":"<strong>Andrew Dasher, PhD, University of Texas Police Department - Houston<\/strong>\r\n\r\n<strong>Robert Haynes, MPA, University of Texas Police Department - Houston<\/strong>","main_category":"Technology","legacy_article_id":"","legacy_issue_id":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.4 (Yoast SEO v24.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Overcoming Law Enforcement Data Obstacles - 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\/overcoming-law-enforcement-data-obstacles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Overcoming Law Enforcement Data Obstacles\" \/>\n<meta property=\"og:description\" content=\"RMS (records management system) and CAD (computer-aided dispatch) are ac-ronyms that every police officer has probably heard at least once in his or her career. Similarly, predictive policing, intelligence-led policing, and problem-oriented policing are concepts that law enforcement agencies around the world use on a daily basis to engage their citizens and combat crime. The acronyms and concepts may seem like standalone cogs in the policing machine at first glance, but they are forever linked by a myriad of data pieces that must be obtained, integrated, and acted upon. The problem lies in getting the pieces to interconnect with and communicate accurate information to other technology items. Data, in and of themselves, are not bad. Police departments have always collected data in some fashion. Data collection started with pen and paper, evolved into communication over the telephone or radio, and finally moved into varying digital iterations. The ever-growing need for more and better shared data has consumed all departments, large and small. The drive to implement emerging technologies into police departments is in full force. Citizens want to be able to view crime statistics from their local departments\u2019 webpages, submit a police report over the Internet, and download digital copies of their accident reports, all from the comfort of their living rooms. The age of carbon copy or handwritten police reports is a distant memory (or unheard of) for most law enforcement personnel. The way that a law enforcement agency deals with data can either be a headache or serve as a force multiplier to increase efficiency and citizen interaction. For most police administrators, it is probably a little of both. The challenge is that data can become overwhelming\u2014and can also be a little intimidating\u2014but correct data are the most important foundational cornerstones that must be laid before any new technology can be properly utilized. 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