Problem Solving for Crime Prevention

By Cherney, Adrian | Trends & Issues in Crime and Criminal Justice, May 2006 | Go to article overview

Problem Solving for Crime Prevention


Cherney, Adrian, Trends & Issues in Crime and Criminal Justice


Problem solving methodology is at the heart of crime prevention strategies used by law enforcement agencies across Australia and around the world. The technique typically involves a systematic use of solid data and extensive progress evaluation, with an emphasis on theory, contextuality, and implementation. This paper uses existing literature to highlight the place of problem solving in crime prevention, and the need for flexibility, responsiveness, and the need for an understanding of context in using problem solving techniques. It calls for problem solving to play a greater role in the efforts of criminologists to develop crime prevention programs, and stresses the need for the recording and exchange of information between crime prevention practitioners.

Toni Makkai

Director

Introduction

The adoption of a problem solving methodology is regarded as a core component of crime prevention good practice. The approach is underpinned by a series of steps that involves problem identification and crime data analysis, the selection of strategy objectives and interventions based upon this assessment process, implementation (via some form of partnership) and evaluation of impact (Laycock 2005). Its use is supported by numerous prominent figures, such as the pioneer of problem oriented policing Herman Goldstein (2003) and Ron Clarke (1 997) who regard It as an essential component of any situational crime prevention project. Ekblom (2002) sees the approach as a core element of effective crime prevention planning, with it also broadly underpinning the Communities that Care model of developmental crime prevention (Hawkins & Catalano 1 992).

The aim of this paper is to discuss both the theoretical and practical bases of crime prevention problem solving and in particular to focus on factors that impact on the successful adoption of the problem solving approach. Different models of crime prevention problem solving are briefly outlined. The necessity of building problem oriented responses to crime based on a good understanding of theory is highlighted. In addition, understanding the relevance of context is discussed, particularly as it relates to the process of implementation, as is the need for crime prevention problem solving to be both flexible and responsive to various challenges posed by strategy development and implementation. Knowledge of these issues is important to improving the skills of crime prevention practitioners.

Models of crime prevention problem solving

A number of schematic guides have been developed to assist practitioners to apply the problem solving methodology in practice, the best known being the SARA model (Scan, Analyse, Respond, Assess). Hough and Tilley (1 998) provide a more detailed elaboration (see Figure 1 below), and Ekblom (2003) has developed a problem solving process referred to as the 5 Is model. This involves the gathering and analysis of information on the specific crime problem (Intelligence), selection of the full potential repertoire of responses to address proximate and distal causes of the problem in question (Intervention); action to convert interventions into practical methods (Implementation); mobilisation of key stakeholders and agency participants (Involvement) and evaluation of outcomes (Impact).

An essential thrust of the problem solving approach is the need to be systematic about the process and to avoid jumping to a solution before the problem assessment stage has been carried out. In-depth problem analysis derived from solid data is very much seen as the linchpin of the methodology given that it will determine the success of the final result (i.e. the response and its impact). Evaluation of progress and results and feeding this information into all stages of the problem solving process are likewise regarded as essential to ensuring that it remains iterative (Clarke & Eck 2005, 2003; Forrest, Myhill & Tilley 2005; Sutton 1996). …

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