Modelling Police Community Support Officer Management by Agent-Based Simulation

Davies, Philip Andrew and Johnson, Jeffrey (2021). Modelling Police Community Support Officer Management by Agent-Based Simulation. In: International Research Society for Public Management (IRSPM 2021), 21-23 May 2021, Online.


Complexity theory within public management is becoming a recognised field, but currently without consensus about the contribution it could make to theory and practice. This paper suggests a promising route to engage with management practitioners, in this case within policing by the use of agent-based simulation of a policing team subject to policy changes. Policing has fractal self-similar management structures at all levels. A general methodology is presented to explore the motivational consequences of policies at all levels in these complex multilevel systems as an alternative to 'point-in-time' staff surveys. It is illustrated by the motivation of Police Community Support Officers (PCSOs) at the front line of the police management hierarchy. The computational model is based on qualitative team dynamics data collected using Grounded Theory. This produced ‘behavioural codes’ for aspects of PCSO work, the most prevalent six being taken forward for simulation design: Purpose (feedback on role); Availability of supervision and support; Threat and risk of harm; Relevance to role; Orientation in relation to geographic responsibility; and Lone working (patrolling). The first letter of each phenomena (a vertex) gives the acronym PATROL (a simplex). This greatly facilitated the design and implementation of the simulation and subsequent communication with practitioners. These simplices are highly non-linear in their impact on motivation. We created an interactive computer simulation of the PCSO task execution system, where each task is a combination of simplices called a hypersimplex (a ‘system of systems’). To model motivation and demotivation PATROL simplices are mapped to an ordinal emoticon scale. Combinations of emoticons are mapped into a sequence of pair-wise connected local attractors in order of increasing motivation. PCSO motivation tends to stay in these ‘basins of attraction’ by forces driving it away from adjacent attractors. The boundaries between attractors are characterised by tipping points. Generally, the PCSOs’ motivation stays in the central attractor or above for normal empirically validated settings, based on published job satisfaction survey results. However abnormal situations, such as the sustained absence of sergeant supervision can drive motivation over the tipping points into lower states. Such low motivation has implications for performance, sick leave and retention, and may infect other PCSOs. Modelling PCSO motivation dynamics and computer simulation provide a step towards improved management procedures that avoid unnecessary demotivation. The simulation allows the possible outcome of policies to be explored before they are implemented.

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