David Carter Devon & Cornwall Police (DCP) Jonathan Moizer Plymouth University Business School
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Transcript of David Carter Devon & Cornwall Police (DCP) Jonathan Moizer Plymouth University Business School
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Developing a Police Resourcing Model with System Dynamics:
Group Model Building for a Robust Future
David CarterDevon & Cornwall Police (DCP)
Jonathan MoizerPlymouth University Business School
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Why take a robust future view?
• Disraeli is quoted as saying
“what we anticipate seldom occurs: what we least expect generally happens”
• If we ignore potential then we will waste more
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Introduction • Proposing a system dynamics methodology based
on group model building approaches (TIMETABLE)– Elicited policing system knowledge from a set of
problem owners– Three phase approach to knowledge capture– Scripting used to structure model development with
clients– System dynamics model emerged that allowed DCP to
explore policy alternatives for resourcing patrol-officer function
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Background
• Home Office Directive for more localised training of police probationers
• On-going demand from lower graded incidents not always addressed– Home Office Policing Pledge set 48 hour limit to
‘Routine’ incident response
• Variations in levels of resource available to meet incident demand– Long term trend favouring tenured roles over patrol-
officer roles in DCP
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System Dynamics (SD) applied to Criminal Justice Systems (CJS) &
Policing• Long history of using SD to model CJS & policing
problems– Cost impact of CJS (Space-General Corp. 1965)– Interactions of upstream & downstream system elements
(Fey et al, 1974; Bard, 1977; Bernstein, 1994; Olaya et al, 2008)
– Policing & criminal phenomena (Coyle, 1996)– Policing & performance (Newsome, 2008)– Police strategy making (Howick & Eden, 2011)
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Ways of Exploring Uncertain Futures for Policing
Adapted from Börjeson (2006); Bishop et al, 2007; Duinker & Greig, 2007
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SD & Group Model Building (GMB)
• Long history of building client based SD models with groups of problem owners (e.g. Vennix, 1996, 1999; Rouette et al, 2002; Luna-Reyes & Andersen; Etiënne et al, 2011…)
• Seen growth of SD model building with clients • GMB approach
– Scripting (clarity & speed) – Ackermann et al (2010)– Different tasks (e.g. facilitation, model building)
Richardson & Andersen (1995)
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PROCESS
OUTCOME
Clear Unclear
Clear Puzzle(Pidd)
Movie Project(Obeng)
Unclear Problem(Pidd)
Mess(Pidd)
Resolving This ‘Messy’ Resourcing Issue
START:Patrol-officer resourcing
>5 years
Types of issue to be resolved (from Fitz-Gerald and Tracy, 2008, p.9)
FINISH:Patrol-officer resourcing
>5 years
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Building the Resourcing Policy Model with the Client Group
• Purpose of modelling effort is to explore DCP patrol-officer resourcing policy• DCP stakeholder input into the model building
– One Manager– Five Mid-ranking Practitioners (Sergeants to Inspectors)– Facilitator/modeller
• Prepared scripts for the group model building effort• Simple, three-phase journey using on GMB (TIMETABLE)
1. Plan potential scenario interactions (PESTEL cross-reference matrix) - MESS2. Agree which causes have what effects - PROBLEM3. Decide where the backlogs (stocks) of work and resources are & how to control (policies)
their flow – PUZZLEa) Developed stock-flow diagram & parameterisation of SD model with groupb) Equations developed outside of group session & working simulation presented to group for further
comment
• Document each step along the way– Record & translate client debates into model structure
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3 Phases of ‘TIMETABLE’
Adapted from Forrester (1994, p.72)
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Process to Dissolve a Mess
TIMETABLE applied to types of issue to be resolved(adapted from Fitz-Gerald and Tracy, 2008, p.9)
PROCESS
OUTCOME
Clear Unclear
Clear Puzzle(Pidd)
TestStructures
(3.SD)
Movie Project(Obeng)
Unclear Problem(Pidd)
ControlBarriers (2.CLD)
Mess (Pidd)
Alternative Futures (1.SP)
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Scenario Cross Impact Matrix (SCIM)
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Cause Barriers Effect on Change
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Process Volume Structures (PVS) capturing service delivery over time
Resultant Process Outcomes
Demand for Process
i/p
o/p
ServiceInputsSupplied
ServiceOutputsConsumed
Pro cess
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Model Building History at DCP TIMETABLE
making aims & approach clear
IPLDP project defining scope
ESIM testing supply/demand
policies
‘Swinging Lamp’ practitioner
stories
Better understood conditions for
enabling change
Rapid appreciation of sustainable performance
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A 3-D View of TIMETABLE
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Emergency Service Incident ModelInteracting rules applyHistorical and
future mix
Compare relative
performances
How effective? What to change?Which option best?Which option 1st?
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Why take a robust future view 2
“ if you can keep your head when all about you are losing theirs (Kipling); it is just possible you have not grasped the pressure on public funds following the credit crunch (Carter)”
• we cannot afford to waste more and therefore need better shared models of our alternative futures
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Summary of the Modelling Process• Maximise client engagement through speed &
enthusiasm• Offers validation of the 3-phase TIMETABLE
journey from mess (scenario plans) through problem (causal maps) to solvable puzzle (system dynamics)
• Produces a scalable methodology that can be used to deal with messy issues through system dynamics modelling
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Any Questions?Contacts for TIMETABLE (& Emergency Service Incident Model – ESIM)[email protected]
Dave [email protected]+44(0) 1503 230 462
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Stock-Flow Structure of Patrol-Officer Supply Sub-Model
recruit
preparing testing
recruit loss
interviewing
patrol
reviewing
guided transferees
learning & guided independent
transferees in
transferees in patrol
learning & guided loss indepedent loss
tenureimproving
patrol exits
tenure exits
transferees to patrol
continuing to full patrol
continuing to tenure
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Stock-Flow Structure of Patrol-Officer Demand Sub-Model
incident rate for non attendance
resolution by phone
routine incident rate
for further resolution
golden period
immediate incidents
immediate incident
rate for first resolution non golden period
immediate incidents
immediate incident rate
for further resolution
non golden period immediate
incident clear up rate
golden period immediate
incident clear up rate
call backlog
weekly call rate
logged patrol incidents to grade
police incident logging rate
golden period routine incidents
unresolved immediate
incident rate
golden period prompt incidents
prompt incident rate
for first resolutionprompt incident rate
for further resolution
non golden period prompt
incident clear up rate
golden period prompt
incident clear up rate
routine incident rate
for first resolution
golden period routine
incident clear up rate
calls resolved without log
unresolved prompt incident rate
non golden period
prompt incidents
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Op Quest Appointments
incident rate for non attendance
resolution by phone
routine incident rate
for further resolution
golden period
immediate incidents
immediate incident
rate for first resolution non golden period
immediate incidents
immediate incident rate
for further resolution
non golden period immediate
incident clear up rate
golden period immediate
incident clear up rate
call backlog
weekly call rate
logged patrol incidents to grade
police incident logging rate
golden period routine incidents
unresolved immediate
incident rate
golden period prompt incidents
prompt incident rate
for first resolutionprompt incident rate
for further resolution
non golden period prompt
incident clear up rate
golden period prompt
incident clear up rate
routine incident rate
for first resolution
golden period routine
incident clear up rate
calls resolved without log
unresolved prompt incident rate
non golden period
prompt incidents
recruit
preparing testing
recruit loss
interviewing
patrol
reviewing
guided transferees
learning & guided independent
transferees in
transferees in patrol
learning & guided loss indepedent loss
tenureimproving
patrol exits
tenure exits
transferees to patrol
continuing to full patrol
continuing to tenure
experience
46fte
-21%