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This Guide is organized around nine fundamental concerns, framed here as questions, which must be addressed when developing a problem-solving capacity within a crime analysis unit. The starting point will vary with the existing resources within the agency and on the extent to which new resources can be deployed. The questions are as follows:
Some of these questions have simple actionable answers; others do not. Many cannot be addressed without the full cooperation of the head of the analysis unit. Still others will require seemingly simple solutions—but in the face of structures that are resistant to development and change. Moreover, care must be taken to ensure that progress does not erode in one area while your attention is directed elsewhere. Attending to each question increases the likelihood that the crime analysis unit will contribute meaningfully to your departmental problem-solving efforts.
Analysts are often asked to perform a variety of non-analytical tasks, including providing computer and software support, secretarial and administrative assistance, and audiovisual and other technological aid. They are often assigned these duties because no one else is available to do them. Consequently, much of their time is spent doing other things. Their skills become more general, rather than specialized, as their time is frittered away on a scattering of requests and demands. If analysts are to perform high order analytical tasks, they must be free from non-analytical duties. Analysts should not be used to cover for departmental shortfalls, technical or otherwise. Neither should they be a crutch for poor resource allocation, training, or time management. Analysts will never fill their proper roles and functions if they cannot be fully committed to them.
In addition to protecting analysts from non-analytical duties, the evolution of problem solving requires that routine analysis be put on hold at certain periods of time. Analysts must be able to dedicate time and effort to learning the new tools and methods needed for problem solving. They must consistently sharpen their skills and knowledge over time.
Too often, crisis management and recurring obligations (e.g., weekly briefings or monthly reports), even when appropriately assigned, can prevent the development of new skills and capacities. Moreover, developing the specialized skills necessary for problem analysis requires ongoing assignment of staff. Consistency and balance in personnel is critical to ensuring that skills are developed and enhanced. The biggest long-term risk to analysts is a lack of professional progression.
Any group of analysts possesses inconsistent skill sets; and indeed, varying skills can be of great benefit to the unit as a whole if properly managed. However, this can result in a disproportionate workload if some skill or another is more needed or appreciated. Thus, you should avoid relying too heavily on any one analyst or any one particular skill. Rather, attempt to establish consistency through training, information sharing, and collective brainstorming. Skills that are shared among analysts will ensure a more balanced workload.
Most analysts have had only limited exposure to the principles of problem-oriented policing and some traditionally trained analysts have never heard of it at all. They must therefore be trained in the core concepts of problem-oriented policing. As a first step, analysts should be encouraged to read Crime Analysis for Problem Solvers3 and to consult materials on www.popcenter.org, the web site of the Center for Problem-Oriented Policing. They should also be encouraged to attend training sessions and seminars, including the annual Problem-Oriented Policing Conference and the annual meetings of the International Association of Crime Analysts, where they can network with other like-minded analysts. If budgeting allows, consider hiring experts as departmental consultants and allow analysts to visit agencies with a track record of successful problem-oriented projects. Finally, analysts should be given every opportunity to participate as integral members of the team in problem-oriented projects. Practical experience will help them develop the confidence to apply new techniques and might even allow them to find new uses for old techniques.
Most police meetings about problems are not problem-oriented in nature; neither do they provide the same experience as problem-oriented policing projects. Managers should guide these projects to ensure that problem-solving efforts remain at the core of the approach. A cornerstone of effective guidance and supervision for crime analysts is nurturing a relentless and methodical approach to attacking problems. Problem-oriented methods do not always lead to quick success and, in fact, trial and error learning is expected. This is in contrast to traditional policing approaches, which focus on immediate responses to changing needs and circumstances. Analysts who are used to operating along such traditional lines often struggle with the longer term needs of problem-oriented projects. Scope creep, loss of focus, and confusing tactical responses can fray the edges of any effort. When combined with the myriad challenges associated with real world problem solving, these seemingly minor difficulties can lead to disappointment and disillusion.
It is therefore vital to instill the methodical long-term nature of problem-oriented policing in a team accustomed to non-methodical, short term tasks. When this is done successfully, analysts can sometimes be the glue that holds a project together because their methodical operations push the project from one stage to the next.
Traditional analytical skills closely mirror those needed by problem analysts. Both need timely and accurate information and both engage in similar analyses to distill data. Police data is heavily relational; analysts of both types must understand the nature of these relationships and how they can be deconstructed. However, problem solving calls for a different application of technology and data than traditional tactical analysis. In particular, it requires the analyst to expand the breadth and scope of the data in order to be able to, (1) analyze the diverse factors that contribute to a particular problem and, (2) assess the effectiveness of the responses implemented.
Good data is at the heart of good analysis and it is important that analysts dedicate time to establishing a timely flow of appropriate data. Because data collection is rarely done with sophisticated analysis in mind, data must often be processed for analytical needs. Moreover, because the data flow must be dynamic, changes to data processing are often necessary. As analysts get more sophisticated and the analytical process gets more streamlined, so should the data. Without consistent and accurate data, much of the time and money spent on tools and techniques will be wasted. Flexibility and creativity are more likely to produce better and faster results than are more complicated or sophisticated software products and techniques.
Problem solving also sometimes requires analysts to seek out or even create data sets that have never existed before. Analysts engaged in real world problem solving are less reliant on traditionally-structured quantitative data. Qualitative and unstructured data (including free-form field reports and other unstructured narratives) take on great importance in many problem-solving efforts. Problem-solving analysts must be adept at sifting and shaping these data sets into a cohesive form that can provide meaningful insight into a specific crime problem. But they must also possess an understanding of traditional policing practices and must be able to synthesize their analytical training with traditional theories, data, and technologies. It is this combination of skills—analytical and practical—that makes problem-solving analysts so valuable.
This guide does not consider individual software applications, databases and data structures, or specific analytical techniques. In fact, the only professional consensus seems to be in the types of technologies that are useful—i.e., relational databases, spreadsheets, statistical software, geographic information systems, web technologies, reporting software, link software, text analytics software, online analytical processing (OLAP) software, and so forth. There is certainly no consensus regarding specific hardware or software applications; the best methods for storing, retrieving, and processing various data types; or the best methodologies to apply to specific problems. Moreover, any consensus would likely be short-lived, as all of these applications and processes are subject to dramatic change as technology and methodology evolve due to cost, scale, experience, and any number of other factors.
Automation and newer, easier to use tools are a constant; data storage, structures, and mining techniques change. Analysts should be at the forefront of these evolving skills and technologies. They must be able to take advantage of everything that the current technologies offer while at the same time having the freedom to explore advances that will allow them to maximize their effectiveness in the future. Managers should work to create a professional environment that allows analysts to remain current with evolving technologies so that they can converse fluently with information technology personnel.
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