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A decision support system and a mathematical model for strategic workforce planning in consultancies

Author

Listed:
  • N. Llort

    (Universitat Politecnica de Catalunya, BarcelonaTech)

  • A. Lusa

    (Universitat Politecnica de Catalunya, BarcelonaTech)

  • C. Martínez-Costa

    (Universitat Politecnica de Catalunya, BarcelonaTech)

  • M. Mateo

    (Universitat Politecnica de Catalunya, BarcelonaTech)

Abstract

Strategic staff planning in consultancies is a major problem that directly affects the firm’s performance and capacity for dealing with projects appropriately. Furthermore, the decisions taken now will have long term consequences, because consultants are highly qualified workers who need very long learning periods to achieve enough expertise. In other words, the size and composition of the future workforce depends on the decisions taken today. It is important to underline that the system anticipates future capacity adjustment in response to forecasted demand requirements; therefore, it is flexible to plan the workforce in different scenarios and time horizons. This paper proposes a decision support system based on a mathematical optimization model for solving strategic staff planning, taking the company’s strategies, policies and objectives into account and optimizing both the costs and the staff composition. The tool is tested by applying it in an office belonging to a multinational consulting firm.

Suggested Citation

  • N. Llort & A. Lusa & C. Martínez-Costa & M. Mateo, 2019. "A decision support system and a mathematical model for strategic workforce planning in consultancies," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 497-523, June.
  • Handle: RePEc:spr:flsman:v:31:y:2019:i:2:d:10.1007_s10696-018-9321-2
    DOI: 10.1007/s10696-018-9321-2
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    References listed on IDEAS

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    Cited by:

    1. Jose Pedro Garcia-Sabater & Julien Maheut & Angel Ruiz & Julio Juan Garcia-Sabater, 2020. "A Framework for Capacity and Operations Planning in Services Organizations Employing Workers with Intellectual Disabilities," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    2. Pieter Smet & Annelies Lejon & Greet Vanden Berghe, 2021. "Demand smoothing in shift design," Flexible Services and Manufacturing Journal, Springer, vol. 33(2), pages 457-484, June.

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