For registration information about upcoming trainings, please visit compstat.umd.edu.
There are six types of training, each lasting for 8 hours. Following is a description of each type of training, suggestions for potential attendees, and registration directions. We recommend agencies attempt to send personnel to the same trainings sessions when possible.
This Training is geared towards police first-line supervisors, managers, and command staff. It will provide a discussion of the roles of the various ranks in the police agency in the CompStat process in using crime analysis, conducting crime reduction responses, and holding people accountable. It will also cover how realistic expectations are based on crime analysis results, how a structure of systematic review is achieved through meetings, how crime reduction processes are documented, and how success is evaluated.
This Training presents an overview of the characteristics, principles, and processes of CompStat and presents approaches for implementation which focus on best practices. It outlines the organizational structure and personnel roles as well as the development of organizational goals and performance measures that serve as the foundation of the CompStat process. The discussion focuses on how crime reduction strategies are employed for a range of short-term and long-term problems by varying ranks within a police organization, as well as how a CompStat structure of meetings is used to hold personnel accountable for these responses.
This seminar is for police who are looking for innovative ways to institutionalize crime reduction activities in their agencies. Research on effective policing models is discussed as well as how these models such as CompStat, Hotspots/Disorder Policing, Problem-Oriented Policing, and Intelligence-Led Policing can be integrated and implemented in a police organization to reduce and prevent crime. The discussion will also highlight how small adjustments to the organizational structure, creating standards, and establishing expectations for personnel are made to ensure analysis is being used to drive crime reduction responses and that individuals and divisions are being held accountable.
This Training will provide direction for collecting data and creating specific crime analysis and mapping products that are used in the CompStat process. The Training will cover specific products that are effective and useful for short-term and long-term crime reduction strategies and the evaluation of those strategies. Throughout the Training, practical examples, and situations will be used to highlight each product.
This Training is geared towards police managers and command staff in agencies that are looking to or have already implemented CompStat. This Training is a working session, in which attendees will apply the concepts taught in the prerequisite Training sessions (see prerequisites below) to their own agency. The trainers and trainees will discuss barriers and supports of an agency’s CompStat process as well as adjustments to each agency’s organizational structure to implement or improve CompStat in their agency. The participants will leave the Training with a specific list of suggested changes/improvements for their agency’s current management process.
This Training covers performance management in a full-day workshop that combines lecture and practical exercises. The lecture covers how performance management works, why it is a better approach than traditional police management models, and how to implement it in your agency. In the practical exercises, participants work in small groups that resemble a planning team as they use the six drivers of performance management to develop a model for a simulated police agency. This introduces executives and upper management to a systematic way to manage the agency while taking account of certain constraints. The instructor guides each group to ensure they comprehend how the model fits together and whether they considered alternatives to their measures.
For registration and information about upcoming trainings please visit compstat.umd.edu.