Can Police Optimize Resource Allocation in Lean Times? An Efficiency-Based Approach

Police agencies face significant staffing shortages due to increased resignations and retirements following the George Floyd protests and the COVID-19 pandemic. A method called Inverse Data Envelopment Analysis (InvDEA) can be used to estimate how policing inputs, such as officers, staff, and vehicles, can be reallocated to increase policing outputs, such as arresting offenders, clearing crimes, or responding to emergencies. Using a simulation of a police agency with 150 sectors, the author showed that it was possible to reallocate officers and civilians from inefficient to efficient sectors to significantly improve performance without any additional inputs.

Authors

Publication Details

Journal
Applied police briefings :
Published
2024-09-04
DOI
https://doi.org/10.22215/apb.v1i2.5003
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Can Police Optimize Resource Allocation in Lean Times? An Efficiency-Based Approach

Erik Alda
Applied police briefings :
Supply Chain and Inventory Management
article

Can Police Optimize Resource Allocation in Lean Times? An Efficiency-Based Approach

Erik Alda
article en

Abstract

Police agencies face significant staffing shortages due to increased resignations and retirements following the George Floyd protests and the COVID-19 pandemic. A method called Inverse Data Envelopment Analysis (InvDEA) can be used to estimate how policing inputs, such as officers, staff, and vehicles, can be reallocated to increase policing outputs, such as arresting offenders, clearing crimes, or responding to emergencies. Using a simulation of a police agency with 150 sectors, the author showed that it was possible to reallocate officers and civilians from inefficient to efficient sectors to significantly improve performance without any additional inputs.

Applied police briefings :Vol. 1(2)
Openalex Percentile: Top 67%
Supply Chain and Inventory Management
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