Risk Managed Demand: Proof of Concept for an Evidence-Based Framework, Operationalized to meet the Demand for Order in a Civil Society
type: CreativeWork
description: Is it safe to send a non-police “responder” to calls traditionally handled by police (911 in the US, 999 in the UK)? If so, what calls (categories and/or types) should be considered? How should they be identified (criteria) and with what operational procedures or systems? This study explores the viability of a diversified response (e.g., differential police response, co-response, alternative first response) to the more than 240 million calls received by 911 in the United States, annually. Observations made as early as the 1960s suggest the answer, at least with the benefit of hindsight, is unequivocally “yes.’’ The practicality of which is another matter. How and when to send a diversified response requires a systematic approach to risk management and call triage. A solution to what we term the “Ratcliffe Paradox,” whereby opportunities for a non-police response require a police response to identify them. This study leverages principles of risk management from commercial aviation and commercial technology from “intelligent call centers” to achieve three objectives, each of which is the subject of peer-reviewed publication either accepted or pending decision after having completed requested revision: 1) The first study analyzes three years of data from Seattle, Washington (USA) (n=727,423). Nearly half (48.9%) of the 356 types of call conventionally handled by police could be safely managed by a system of diversified response, rather than the current “all-hazards responder” approach. This Risk Managed Demand (Risk Managed Demand) framework could optimize resource allocation, potentially recovering up to 26% of police capacity expended on what are ultimately determined to be non-police calls. 2) The second study demonstrated “proof-of-concept” that the Seattle Police Department’s newly developed Intelligent Risk Management (IRM) system and established it could safely and effectively triage (i.e., identify) opportunities for a diversified response. This system is based…
abstract: Is it safe to send a non-police “responder” to calls traditionally handled by police (911 in the US, 999 in the UK)? If so, what calls (categories and/or types) should be considered? How should they be identified (criteria) and with what operational procedures or systems? This study explores the viability of a diversified response (e.g., differential police response, co-response, alternative first response) to the more than 240 million calls received by 911 in the United States, annually. Observations made as early as the 1960s suggest the answer, at least with the benefit of hindsight, is unequivocally “yes.’’ The practicality of which is another matter. How and when to send a diversified response requires a systematic approach to risk management and call triage. A solution to what we term the “Ratcliffe Paradox,” whereby opportunities for a non-police response require a police response to identify them. This study leverages principles of risk management from commercial aviation and commercial technology from “intelligent call centers” to achieve three objectives, each of which is the subject of peer-reviewed publication either accepted or pending decision after having completed requested revision: 1) The first study analyzes three years of data from Seattle, Washington (USA) (n=727,423). Nearly half (48.9%) of the 356 types of call conventionally handled by police could be safely managed by a system of diversified response, rather than the current “all-hazards responder” approach. This Risk Managed Demand (Risk Managed Demand) framework could optimize resource allocation, potentially recovering up to 26% of police capacity expended on what are ultimately determined to be non-police calls. 2) The second study demonstrated “proof-of-concept” that the Seattle Police Department’s newly developed Intelligent Risk Management (IRM) system and established it could safely and effectively triage (i.e., identify) opportunities for a diversified response. This system is based…
author: Atherley, Loren
keywords: Policing, Risk Management, Evidence-Based Policing, Artificial Intelligence, Machine Learning
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/ebb1ecdf-947e-4277-8d3d-95c9f61d8bc3/download
license: http://purl.org/NET/rdflicense/allrightsreserved
date published: 2025-02-18
date modified: 2026-07-22T22:24:28Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.118937