- Start date: 25 February 2019
- End date: 24 August 2019
- Funder: Alan Turing Institute
- Primary investigator: Dr Daniel Birks
The 21st century has seen policing agencies become involved in an increasingly diverse range of roles, often while managing relatively restricted resources. Consequently, a key priority for applied policing relates to better understanding and anticipating changes in demand. But the challenges to policing are not limited to there simply being too few resources. Problems vary in terms of scale, harm and whether responses are dealt with locally, regionally or require national coordination. There are priority areas for which demand needs to be better understood (and met) however, demand is poorly understood for other areas.
As a result, models of police resourcing are required to allow police agencies to better understand the drivers of demand and best optimise the allocation of existing resources to minimise threat, risk and harm to the community. An array of factors internal and external to police organisations, often highly interdependent, influence demand, and are therefore difficult to model using traditional analytical techniques.
This project aims to assess how data-driven agent-based models might be applied to better understand the dynamics of police demand and resourcing, with the goal to assess the viability of these techniques for developing decision support tools capable of analysing ongoing, and forecasting future, police demand.
The project will involve a rapid scoping exercise to analyse data sources describing the drivers of, and responses to, police demand. It will also develop exploratory computational models that seek to simulate police demand and resourcing dynamics at both individual and organisational scales.
Co-investigators are based at the School of Geography and UCL, and the project will relevant members of the UK police services and national agencies. The project is funded by the UKRI Strategic Priorities Fund under the theme of Criminal Justice.