David Carter Devon & Cornwall Police (DCP) Jonathan Moizer Plymouth University Business School

1. Developing a Police Resourcing Model with System Dynamics: Group Model Building for a Robust Future David Carter Devon & Cornwall Police (DCP) Jonathan Moizer Plymouth University Business School

2. 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

3. 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

4. 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

5. 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)

6. Ways of Exploring Uncertain Futures for Policing Adapted from Börjeson (2006); Bishop et al, 2007; Duinker & Greig, 2007

7. 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)

8. OUTCOME Clear Unclear Clear Puzzle Movie Project ( Pidd ) ( Obeng ) P R Unclear Problem Mess O ( Pidd ) ( Pidd ) C E S S Resolving This ‘Messy’ Resourcing Issue FINISH: Patrol-officer resourcing >5 years START: Patrol-officer resourcing >5 years Types of issue to be resolved (from Fitz-Gerald and Tracy, 2008, p.9)

9. 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) • Plan potential scenario interactions (PESTEL cross-reference matrix) - MESS • Agree which causes have what effects - PROBLEM • Decide where the backlogs (stocks) of work and resources are & how to control (policies) their flow – PUZZLE • Developed stock-flow diagram & parameterisation of SD model with group • 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

10. 3 Phases of ‘TIMETABLE’ Adapted from Forrester (1994, p.72)

11. OUTCOME Clear Unclear Clear Puzzle Movie Project ( Pidd ) (Obeng) Test Structures P h ( 3.SD) R O Unclear Problem Mess ( Pidd ) C ( Pidd ) E Control Alternative S Barriers Futures ß ß S (2.CLD) (1.SP) Process to Dissolve a Mess TIMETABLE applied to types of issue to be resolved (adapted from Fitz-Gerald and Tracy, 2008, p.9)

12. Scenario Cross Impact Matrix (SCIM)

13. Cause Barriers Effect on Change

14. Process Volume Structures (PVS) capturing service delivery over time i/p Service Inputs Supplied Demand for Process Resultant Process Outcomes Pro cess Service Outputs Consumed o/p

15. Model Building History at DCP TIMETABLE making aims & approach clear ESIM testing supply/demand policies IPLDP project defining scope ‘Swinging Lamp’ practitioner stories Rapid appreciation of sustainable performance Better understood conditions for enabling change

16. A 3-D View of TIMETABLE

17. Emergency Service Incident Model Interacting rules apply Compare relative performances Historical and future mix How effective? Which option best? Which option 1st? What to change?

18. 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

19. 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

20. Any Questions? Contacts for TIMETABLE (& Emergency Service Incident Model – ESIM) Jonathan.Moizer@plymouth.ac.uk Dave Carter enquiries@dandco.co.uk www.dandco.co.uk +44(0) 1503 230 462

21. Stock-Flow Structure of Patrol-Officer Supply Sub-Model

22. Stock-Flow Structure of Patrol-Officer Demand Sub-Model

23. Op Quest Appointments 46fte experience -21%