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Enhanced performance measurement using OR: a case study

  • Case-Oriented Paper
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Journal of the Operational Research Society

Abstract

The case study described in this paper aims to illustrate how qualitative and quantitative system dynamics modelling and multicriteria analysis can be used in an integrated way to enhance the process of performance measurement and management in the radiotherapy department of a major UK cancer treatment centre. The complexity of the radiotherapy process and its significance for patients present particular challenges for performance measurement and management. The paper discusses the benefits arising and the practical difficulties faced in the study.

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References

  • Ackermann F, Belton V, Shafti S and Wisniewski M (2005). Building a balanced scorecard the OR way. Paper presented at IFORS 2005, Hawaii, USA.

  • Akkermans HA and van Oorschot KE (2005). Relevance assumed: A case study of balanced scorecard development using system dynamics. J Opl Res Soc 56: 931–941.

    Article  Google Scholar 

  • Andersen DF and Rohrbaugh J (1992). Some conceptual and technical problems in integrating models of judgement with simulation models. IEEE T Syst Man Cyb 22(1): 21–34.

    Article  Google Scholar 

  • Belton V and Stewart TJ (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Kluwer Academic Publishers: London.

    Book  Google Scholar 

  • Bititci US, Suwignjo P and Carrie AS (2001). Strategy management through quantitative modelling of performance measurement systems. Int J Prod Econ 69: 15–22.

    Article  Google Scholar 

  • Bititci US, Turner T and Begemann C (2000). Dynamics of performance measurement systems. Int J Opns Prod Mngt 20: 692–704.

    Article  Google Scholar 

  • Bohanec M, Zupan B and Rajkovic V (2000). Applications of qualitative multi-attribute decision models in health care. Int J Med Inform 58: 191–205.

    Article  Google Scholar 

  • Boland T and Fowler A (2000). A systems perspective of performance management in public sector organisations. Int J Prod Syst Mngt 13: 417–446.

    Google Scholar 

  • Bots PWG and Hulshof S (2000). Designing multi-criteria decision analysis processes for priority setting in health policy. J Multi-Crit Decis Anal 9(1-3): 56–75.

    Article  Google Scholar 

  • Brailsford SC and Harper P (eds) (2006). OR in health. Special Issue of Eur J Opl Res, forthcoming.

  • Brailsford SC, Lattimer VA, Tarnaras P and Turnbull JC (2004). Emergency and on-demand health care: Modelling a large complex system. J Opl Res Soc 55(1): 34–42.

    Article  Google Scholar 

  • Brans JP, Macharis C, Kunsch PL, Chevalier A and Schwaninger M (1998). Combining multicriteria decision aid and system dynamics for the control of socio-economic processes. An iterative real-time procedure. Eur J Opl Res 109: 428–441.

    Article  Google Scholar 

  • Chevalier A, Kunsch PL and Brans JP (2004). A contribution to the development of strategic control and planning instruments: An acquisition case study. Int Trans Opl Res 11(2): 155–168.

    Article  Google Scholar 

  • Clinton BD, Webber SA and Hassell JM (2002). Implementing the balanced scorecard using the AHP. Mngt Acc Quart 3(3): 1–11.

    Google Scholar 

  • Commission for Health Improvement (2001). National Service Framework Assessments No. 1—NHS Cancer Care in England and Wales. Commission for Health Improvement: London.

  • Coyle RG (1996). System Dynamics Modelling: A Practical Approach. Chapman & Hall: London.

    Book  Google Scholar 

  • Da Silveira G and Slack N (2001). Exploring the trade-off concept. Int J Opns Prod Mngt 21(7): 949–964.

    Article  Google Scholar 

  • Dangerfield BC and Roberts CA (eds) (1999). Health and health care dynamics. Special issue of the Sys Dynam Rev 15(3).

  • Davies R and Bensley D (eds) (2005). Meeting health challenges with OR. Special issue of J Opl Res Soc 56(2).

  • Davis A and O'Donnell J (1997). Modelling complex problems: System dynamics and performance measurement. Mngt Acc 75(5): 18–20.

    Google Scholar 

  • Dennis RL, Stewart TR, Middleton P, Downton M, Ely D and Keeling MC (1983). Integration of technical and value issues in air quality policy formation: A case study. Socio Econ Plann Sci 17(3): 95–108.

    Article  Google Scholar 

  • Department of Health (1999). A Survey of Radiotherapy Services in England. Department of Health: London.

  • Department of Health (2000). The NHS Cancer Plan—A Plan for Investment, A Plan for Reform. Department of Health: London.

  • Department of Health (2001). A Survey of Radiotherapy Services in England and Wales (2001). Department of Health: London.

  • Department of Health (2002). A Survey of Radiotherapy Services in England and Wales (2002). Department of Health: London.

  • Dolan JG (2005). Patient priorities in colorectal cancer screening decisions. Health Expect 8: 334–344.

    Article  Google Scholar 

  • Dyson RG (2000). Strategy, performance and operational research. J Opl Res Soc 51(1): 5–11.

    Article  Google Scholar 

  • Fitzgerald L, Johnston R, Brignall S, Silvestro R and Voss C (1991). Performance Measurement in Service Businesses. CIMA Publishing: London.

    Google Scholar 

  • Forrester JW (1961). Industrial Dynamics. MIT Press: Cambridge, MA.

    Google Scholar 

  • Gardiner PC and Ford A (1980). Which policy run is best, and who says so? In: Legasto AA, Forrester JW and Lyneis JM (eds). System Dynamics: TIMS Studies in the Management Sciences, vol. 14. North-Holland: Amsterdam. pp 241–257.

  • Gruver WA, Ford A and Gardiner PC (1984). Public policy analysis using three systems science techniques. IEEE Trans Syst Man Cybernet SMC-14: 355–361.

    Article  Google Scholar 

  • Hammond KR, Klitz JK and Cook RL (1978). How systems analysts can provide more effective assistance to the policy maker. J Appl Syst Anal 5(2): 111–136.

    Google Scholar 

  • Hammond KR, Mumpower JL and Smith TH (1977). Linking environmental models with models of human judgment: A symmetrical decision aid. IEEE Trans Syst Man Cybernet SMC-7: 358–367.

    Article  Google Scholar 

  • Kaplan RS and Norton DP (1992). The balanced scorecard—Measures that drive performance. Harvard Bus Rev 70(1): 71–79.

    Google Scholar 

  • Keeney RL and Raiffa H (1976). Decisions with Multiple Objectives. Wiley & Sons: New York.

    Google Scholar 

  • Kunsch PL, Chevalier A and Brans JP (2001). Comparing the adaptive control methodology (ACM) to the financial planning practice of a large international group. Eur J Opl Res 132: 479–489.

    Article  Google Scholar 

  • Kunsch PL, Springael J and Brans JP (1999). An adaptive multicriteria control methodology in sustainable development case study: A CO2 ecotax. Belgian J Opns Res Statist Comput Sci 39: 109–143.

    Google Scholar 

  • Lane DC, Monefeldt C and Rosenhead JV (2000). Looking in the wrong place for healthcare improvements: A system dynamics study of an accident and emergency department. J Opl Res Soc 51: 518–531.

    Article  Google Scholar 

  • Lynch RL and Cross KF (1991). Measure Up! The Essential Guide to Measuring Business Performance. Mandarin: London.

    Google Scholar 

  • Mapes J, New C and Szwejczewski M (1997). Performance trade-offs in manufacturing plants. Int J Opns Prod Mngt 17(10): 1020–1033.

    Article  Google Scholar 

  • Min H, Mitra A and Oswald S (1997). Competitive benchmarking of health care quality using the analytic hierarchy process: An example from Korean cancer clinics. Socio Econ Plann Sci 31(2): 147–159.

    Article  Google Scholar 

  • Mosmans A, Praet JC and Dumont C (2002). A decision support system for the budgeting of the Belgian health care system. Eur J Opl Res 139: 449–460.

    Article  Google Scholar 

  • Mumpower J, Veirs V and Hammond KR (1979). Scientific information, social values, and policy formation: The application of simulation models and judgment analysis to the Denver regional air pollution problem. IEEE Trans Syst Man Cybernet SMC-9: 464–476.

    Article  Google Scholar 

  • Neely A, Adams C and Crowe P (2001). The performance prism in practice. Measur Bus Excell 5(2): 6–13.

    Article  Google Scholar 

  • Neely A, Adams C and Kennerley M (2002). The Performance Prism: The Scorecard for Measuring and Managing Business Success. Financial Times Prentice Hall: London.

    Google Scholar 

  • NHS Executive (1999). The NHS Performance Assessment Framework. NHS Executive: London.

  • Olson DL, Dimitrova-Davidova P and Stoykov I (2005). System dynamics model of a transition firm. Manage Fin 31(3): 67–80.

    Google Scholar 

  • Rabelo L, Eskandari H, Shalan T and Helal M (2005). Supporting simulation-based decision making with the use of AHP analysis. In: Kuhl ME, Steiger NM, Armstrong FB and Joines JA (eds). Proceedings of the 2005 Winter Simulation Conference. Orlando: Florida, Society for Computer Simulation International, San Diego, CA, pp 2042–2051.

    Google Scholar 

  • Rangone A (1996). An analytical hierarchy process framework for comparing the overall performance of manufacturing departments. Int J Opns Prod Mngt 16(8): 104–119.

    Article  Google Scholar 

  • Reagan-Cirincione P, Schuman S, Richardson GP and Dorf SA (1991). Decision modeling: Tools for strategic thinking. Interfaces 21(6): 52–65.

    Article  Google Scholar 

  • Richardson GP (1986). Problems with causal-loop diagrams. Syst Dynam Rev 2(2): 158–170.

    Article  Google Scholar 

  • Richardson GP (1997). Problems in causal-loop diagrams revisited. Syst Dynam Rev 13(3): 247–252.

    Article  Google Scholar 

  • Rosas-Flunger R (2000). The system dynamics approach and the methodology for multicriteria decision aid as tools for organizational learning. Proceedings of the 18th International Conference of the System Dynamics Society, Bergen, Norway, System Dynamics Society, Albany, NY, pp 176–177.

    Google Scholar 

  • Santos SP, Belton V and Howick S (2002). Adding value to performance measurement by using system dynamics and multicriteria analysis. Int J Opns Prod Mngt 22: 1246–1272.

    Article  Google Scholar 

  • Schmidt MJ and Gary MS (2002). Combining system dynamics and conjoint analysis for strategic decision making with an automotive high-tech SME. Syst Dynam Rev 18: 359–379.

    Article  Google Scholar 

  • Shutler M and Storbeck J (2002). Performance management (Part Special Issue Editorial). J Opl Res Soc 53: 245–246.

    Article  Google Scholar 

  • Smith PC and Goddard M (2002). Performance management and operational research: A marriage made in heaven? J Opl Res Soc 53: 247–255.

    Article  Google Scholar 

  • Springael J, Kunsch PL and Brans JP (2002). A multicriteria based system dynamics modelling of traffic congestion caused by urban commuters. Central European J Opns Res 10(1): 81–97.

    Google Scholar 

  • Sterman JD (2000). Business Dynamics Systems Thinking and Modeling for a Complex World. McGraw-Hill: London.

    Google Scholar 

  • Tatikonda LU, Tatikonda RJ (1998). We need dynamic performance measures. Mngt Acc. September: 49–53.

  • von Winterfeldt D and Edwards W (1986). Decision Analysis and Behavioural Research. Cambridge University Press: Cambridge.

    Google Scholar 

  • Wisner JD and Fawcett SE (1991). Linking firm strategy to operating decisions through performance measurement. Prod Invent Mngt 32(3): 5–11.

    Google Scholar 

  • Wolstenholme EF (1999). A patient flow perspective of UK health services: Exploring the case for new ‘intermediate care’ initiatives. Syst Dynam Rev 15: 253–271.

    Article  Google Scholar 

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Acknowledgements

Financial support for the research carried out by Sérgio P Santos was gratefully received from the Fundação para a Ciência e a Tecnologia, under grant SFRH/BD/823/2000. Acknowledgement is also due to the staff at the Cancer Centre that participated in this study. A very special thank you is due to Professor Alan Rodger, Dr Adam Bryson, Ms Isobel Neil and Ms Franky Milne for their help, time and commitment, without which this study would not have been possible.

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Santos, S., Belton, V. & Howick, S. Enhanced performance measurement using OR: a case study. J Oper Res Soc 59, 762–775 (2008). https://doi.org/10.1057/palgrave.jors.2602397

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  • DOI: https://doi.org/10.1057/palgrave.jors.2602397

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