What is CompStat?

CompStat and Its Next Generation

In 1994, Police Commissioner William Bratton introduced a data-driven management model in the New York City Police Department called CompStat, which has been credited with decreasing crime and increasing quality of life in New York City over the last eighteen years (Bratton, 1998; Kelling & Bratton, 1998; Shane, 2007). Due to its success in New York, CompStat has diffused quickly across the United States and has become a widely embraced management model focused on crime reduction.

In 1999 and 2000, over a third of agencies with 100 or more officers reported implementing a “CompStat-like” program (Weisburd, Mastrofski, McNally, Greenspan, & Willis, 2003). In fact, due to CompStat’s flexibility, Maryland’s Governor Martin O’Malley used this model to create CitiStat when he was Mayor of Baltimore and now StateStat for the state of Maryland, innovatively expanding the CompStat model as a means to oversee and manage multiple government agencies (Fillichio, 2005; Fenton, 2007). Recognizing the difficulty police agencies have had with implementing CompStat effectively, the Maryland CompStat-on-Demand initiative advocates a “next generation” model of CompStat that seeks to improve upon how CompStat has been implemented over the last fifteen years.

What follows is a brief overview of the original CompStat components as well as a description of the Stratified Model that is the foundation of Maryland’s current CompStat-on-Demand initiative.

CompStat: A Brief Overview

The CompStat model is a management process within a performance management framework that synthesizes analysis of crime and disorder data, strategic problem solving, and a clear accountability structure. Ideally, CompStat facilitates accurate and timely analysis of crime and disorder data, which is used to identify crime patterns and problems. Based on this analysis, tailored responses are implemented through rapid deployment of personnel and resources. An accountability structure is key to ensuring the analysis is acted upon and the responses are implemented correctly as well as assessing whether responses are effective in reducing crime and disorder (Weisburd et al., 2003).

The CompStat process is guided by four principles, which are summarized as follows (see McDonald, 2002; Shane, 2007; & Godown, 2009):

Accurate and timely intelligence (i.e., “Know what is happening.” (Godown, 2009)): In this context, crime intelligence relies on data primarily from official sources, such as calls for service, crime, and arrest data. This data should be accurate and available as close to real-time as possible. This crime and disorder data is used to produce crime maps, trends, and other analysis products. Subsequently, command staff uses these information products to identify crime problems to be addressed.

Effective tactics (i.e., “Have a plan.” (Godown, 2009)): Relying on past successes and appropriate resources, command staff and officers plan tactics that will respond fully to the identified problem. These tactics may include law enforcement, government, and community partners at the local, state, and federal levels. A CompStat meeting provides a collective process for developing tactics as well as accountability for developing these tactics.

Rapid deployment (i.e., “Do it quickly.” (Godown, 2009)): Contrary to the reactive policing model, the CompStat model strives to deploy resources to where there is a crime problem now, as a means of heading off the problem before it continues or escalates. As such, the tactics should be deployed in a timely manner.

Relentless follow-up and assessment (i.e., “If it works, do more. If not, do something else.” (Godown, 2009)): The CompStat meeting provides the forum to “check-in” on the success of current and past strategies in addressing identified problems. Problem-focused strategies are normally judged a success by a reduction in or absence of the initial crime problem. This success or lack thereof, provides knowledge of how to improve current and future planning and deployment of resources.

CompStat’s Next Generation: The Stratified Model of Problem Solving, Analysis, and Accountability

Current research on CompStat suggests that the four principles of CompStat are often not implemented as originally intended. Many law enforcement agencies use CompStat to merely reinforce traditional features of the police bureaucracy, including authoritarianism, hierarchy, and control (Willis, Mastrofski & Weisburd, 2004, 2007). Agencies simultaneously neglect the collaboration, coordination, problem solving, and leadership components of CompStat (DeLorenzi, Shane, & Amendola, 2006; Firman, 2003; Gascon, 2005; Serpas, 2004). Others say that CompStat, as it has been practiced, has been a “review of the numbers,” but that a successful model requires the reengineering of police processes, central data collection, and an understanding of performance management (McDonald, 2002).

The Stratified Model of Problem Solving, Analysis, and Accountability developed by Dr. Rachel Boba Santos and Detective Lieutenant Roberto Santos is an innovative approach to organizational police management that seeks to improve upon CompStat by incorporating the best practices of CompStat, but also those of traditional policing and other police innovations—hotspots policing, problem-oriented policing, and intelligence-led policing. The Stratified Model outlines a structure for institutionalizing crime reduction strategies into the day-to-day practices of the police organization that provides a foundation for holding personnel accountable within a structure of meetings. Quite simply, the Stratified Model significantly improves upon the original CompStat organizational model by incorporating innovative and evidence-based police practices and by more fully specifying the CompStat framework.

In the Stratified Model, the accountability process is carried out through systematic analysis, a routinized tracking system of response strategies, and regular meetings that correspond to the temporal nature of the activity they address. The Stratified Model distinguishes among different levels of crime reduction strategies—from addressing small, incident-centered activity to long-term problems—as well as the different ranks within the police organization that are responsible and held accountable for implementing these strategies. The figure below illustrates the idea that more complex problems are addressed by higher ranks in the organization and that the traditional hierarchical structure of the organization ensures the implementation of crime reduction strategies is taking place.

Stratified Model

By separating and distinguishing the types of problems, different analyses, responses, and accountability are carried out by different personnel within the agency. Accountability within the CompStat process is essential to ensuring that the entire organization implements and maintains its crime reduction efforts consistently and effectively. To accomplish this, the Stratified Model employs a structure of meetings that follow the stratification of problem complexity and the temporal nature of the problem being addressed. This meeting structure consists of:

    Daily meetings/briefings that facilitate action-oriented accountability at the line level for crime reduction strategies implemented for immediate and short-term problems.

    Weekly meetings that facilitate action-oriented accountability where employees from the various divisions of the organization (e.g., patrol, investigations, crime prevention, and media relations) come together to develop, coordinate, and assess responses to short-term problems.

    Monthly meetings that facilitate evaluation-oriented accountability within and among geographic areas. Evaluative crime analysis products are used to assess whether short-term crime reduction strategies are effective, whether long-term problems are emerging, and to monitor the progress of ongoing long-term crime reduction strategies.

    Semi-annual meetings that facilitate evaluation-oriented accountability for the entire organization that are used to examine long-term trends to determine the effectiveness of the agency’s crime reduction approach, to identify new long-term problems to be addressed over the next six months or more, as well as to formulate agency goals and strategies for the coming year(s).

For a detailed description of the Stratified Model and its components, click HERE.

References

Boba, R., & Santos, R. (2011). A police organizational model for crime reduction: Institutionalizing problem solving, analysis, and accountability. Washington, DC: Office of Community Oriented Policing Service.

Bratton, W. J. (1998). Crime is down in New York City: Blame the police. In Norman Dennis (ed.). Zero tolerance: Policing a free society, 2nd ed. (pp.29-42). London: IEA.

DeLorenzi, D., Shane, J.M., & Amendola, K.L. (September 2006). The CompStat process: Managing performance on the pathway to leadership. The Police Chief, 73 (9).

Fenton, J. (2007, February 12). O’Malley installing StateStat: Statistics-based management is coming to Md. government. Baltimore Sun. Retrieved from http://www.baltimoresun.com

Fillichio, C. (2005). Getting ahead of the curve: Baltimore Citistat. Public Manager, 34, 51-53.

Firman, J.R. (July 2003). Deconstructing CompStat to clarify its intent. Criminology & Public Policy, 2 (3), 457-460.

Gascon, G. (May 2005). CompStat plus: In-depth auditing, mentorship, close collaboration. The Police Chief, 72 (5).

Godown, J. (August 2009). The CompStat process: Four principles for managing crime reduction. The Police Chief, 76 (8).

Kelling, G. L., & Bratton, W. J. (1998). Declining crime rates: Insiders’ views on the New York City story. The Journal of Criminal Law and Criminology, 88, 1217-1231.

McDonald, P.P. (2002). Managing police operations: Implementing the New York Crime Control Model – CompStat. Stamford, CT: Wadsworth.

Serpas, R.W. (January 2004). Beyond CompStat: Accountability-driven leadership. The Police Chief, 71 (1).

Shane, J.M. (2007). What every chief executive should know: Using data to measure police performance. Flushing, NY, Looseleaf Law Publications.

Weisburd, D., Mastrofski, S.D., McNally, A., Greenspan, R., & Willis, J.J. (2003). Reforming to preserve: Compstat and strategic problem solving in American policing, Criminology and Public Policy, 2, 421-456.

Willis, J.J., Mastrofski, S.D., & Weisburd, D. (September 2004). CompStat and bureaucracy: A case study of challenges and opportunities for change. Justice Quarterly, 21 (3), 463-496.

Willis, J.J., Mastrofski, S.D. & Weisburd, D. (2007). Making sense of CompStat: A theory-based analysis of organizational change in three police departments. Law & Society Review, 41 (1), 147-188.

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