Planning robust policing futures: modelling using multimethodology

Jonathan Moizer (Faculty of Business, Plymouth University, Plymouth, UK)
David Carter (Faculty of Business, Plymouth University, Plymouth, UK)
Shaofeng Liu (Faculty of Business, University of Plymouth, Plymouth, UK)

Industrial Management & Data Systems

ISSN: 0263-5577

Publication date: 13 April 2015



The resourcing of policing activity is characterised by a level of complexity, particularly where evaluating alternative policy options is concerned. In this paper, a case study using multimethodological modelling to compare alterative policy choice in a group context is outlined with respect to response-patrol officer (RPO) deployment within a UK police force. The paper aims to discuss these issues.


The application of a three phase modelling process is illustrated where scenario planning is used to generate the scope of the system elements to be modelled. This is followed by causal mapping to identify the barriers to improving officer resourcing, and system dynamics modelling is used to simulate the impacts of a range of policy options within this policing function. A group model building approach was applied throughout the modelling phases with an expert group to negotiate a shared view of the structure and dynamics of the resourcing policy challenges.


A fully validated system dynamics model emerged from the multi-phase modelling process which allowed a series of alternative future policy scenarios to be explored and evaluated. Useful policy insights were generated by the system dynamics simulation model which suggested more efficient rules for resource allocation in the police force’s RPO function.


The insights from this case study demonstrates that multi-phase modelling has potential application in policy exploration across a range of emergency service providers whose actions are governed by both variable demand and constrained supply of resource.



Moizer, J., Carter, D. and Liu, S. (2015), "Planning robust policing futures: modelling using multimethodology", Industrial Management & Data Systems, Vol. 115 No. 3, pp. 462-482.

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