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Taking operations strategy into practice: Developing a process for defining priorities and performance measures

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  • Pinheiro de Lima, Edson
  • Eduardo Gouvêa da Costa, Sérgio
  • Reis de Faria, Avides

Abstract

Enterprises' operations systems and environments, characterized by their complexity and dynamics, are challenging operations strategic management models. The study presented in this paper develops a process to integrate operations strategy content to operations performance measurement system design. Essentially, the developed methodology is based on Process Approach (Cambridge Approach) technique that systematizes procedures for generating a performance measures set coherent to operations strategy objectives and also produces a consistent strategy implementation process. To illustrate the development and the application of the proposed design methodology, findings of two case studies related to telecom engineering services companies are used. Results are discussed focusing on testing the proposed methodology in terms of its feasibility, usability, and utility. A refined process, organized in phases, steps, and procedures, is the final result of the presented study.

Suggested Citation

  • Pinheiro de Lima, Edson & Eduardo Gouvêa da Costa, Sérgio & Reis de Faria, Avides, 2009. "Taking operations strategy into practice: Developing a process for defining priorities and performance measures," International Journal of Production Economics, Elsevier, vol. 122(1), pages 403-418, November.
    • Handle: RePEc:eee:proeco:v:122:y:2009:i:1:p:403-418
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    References listed on IDEAS

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    Cited by:

    1. Garcia, Fernanda A. & Marchetta, Martin G. & Camargo, Mauricio & Morel, Laure & Forradellas, Raymundo Q., 2012. "A framework for measuring logistics performance in the wine industry," International Journal of Production Economics, Elsevier, vol. 135(1), pages 284-298.
    2. Agarwal, Renu & Green, Roy & Brown, Paul J. & Tan, Hao & Randhawa, Krithika, 2013. "Determinants of quality management practices: An empirical study of New Zealand manufacturing firms," International Journal of Production Economics, Elsevier, vol. 142(1), pages 130-145.
    3. Wang, Chun-Hsien & Lu, Iuan-Yuan & Chen, Chin-Bein, 2010. "Integrating hierarchical balanced scorecard with non-additive fuzzy integral for evaluating high technology firm performance," International Journal of Production Economics, Elsevier, vol. 128(1), pages 413-426, November.
    4. Fabio Antonio Sartori Piran & Alaércio De Paris & Daniel Pacheco Lacerda & Luis Felipe Riehs Camargo & Rosiane Serrano & Ricardo Augusto Cassel, 2020. "Overall Equipment Effectiveness: Required but not Enough—An Analysis Integrating Overall Equipment Effect and Data Envelopment Analysis," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(2), pages 191-206, June.
    5. Silvestro, Rhian, 2014. "Performance topology mapping: understanding the drivers of performance," International Journal of Production Economics, Elsevier, vol. 156(C), pages 269-282.
    6. Pinheiro de Lima, Edson & Gouvea da Costa, Sergio E. & Angelis, Jannis Jan & Munik, Juliano, 2013. "Performance measurement systems: A consensual analysis of their roles," International Journal of Production Economics, Elsevier, vol. 146(2), pages 524-542.
    7. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.

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