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Competence-based estimation of activity duration in IT projects

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  • Korytkowski, Przemyslaw
  • Malachowski, Bartlomiej

Abstract

The aim of project management is to successfully complete the project on schedule and within budget. Estimation of project activity duration is a key feature of scheduling. The individual activities making up the schedule and the estimation of their duration are crucial for defining the project timetable. The resulting scheduling problem falls into the class of Multi-Skill Resource-Constrained Project Scheduling Problems. In this paper we propose a novel methodology for Activity Duration Estimation in IT projects. The methodology uses the Hierarchical Skill Model and takes into account the experience of project team members, described by required and possessed skills. Skills are modeled as a weighted digraph, and learning curves are used to express individual learning rates. An illustrative example using a software project is provided. Incorporating skill-based modeling into project scheduling results in more precise estimation of actual and future performance.

Suggested Citation

  • Korytkowski, Przemyslaw & Malachowski, Bartlomiej, 2019. "Competence-based estimation of activity duration in IT projects," European Journal of Operational Research, Elsevier, vol. 275(2), pages 708-720.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:2:p:708-720
    DOI: 10.1016/j.ejor.2018.11.061
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    References listed on IDEAS

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    1. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    2. Walter Gutjahr & Stefan Katzensteiner & Peter Reiter & Christian Stummer & Michaela Denk, 2008. "Competence-driven project portfolio selection, scheduling and staff assignment," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 16(3), pages 281-306, September.
    3. Plaza, Malgorzata & Ngwenyama, Ojelanki K. & Rohlf, Katrin, 2010. "A comparative analysis of learning curves: Implications for new technology implementation management," European Journal of Operational Research, Elsevier, vol. 200(2), pages 518-528, January.
    4. Hartmann, Sönke & Briskorn, Dirk, 2010. "A survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 207(1), pages 1-14, November.
    5. Brucker, Peter & Drexl, Andreas & Mohring, Rolf & Neumann, Klaus & Pesch, Erwin, 1999. "Resource-constrained project scheduling: Notation, classification, models, and methods," European Journal of Operational Research, Elsevier, vol. 112(1), pages 3-41, January.
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    Cited by:

    1. Hongbo Li & Hanyu Zhu & Linwen Zheng & Fang Xie, 2024. "Software project scheduling under activity duration uncertainty," Annals of Operations Research, Springer, vol. 338(1), pages 477-512, July.

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