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An empirical project forecasting accuracy framework using project regularity

(2024) ANNALS OF OPERATIONS RESEARCH. 337(2). p.501-521
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Abstract
Forecasting an ongoing project's actual duration is an essential aspect of project management which received considerable attention in the research community. In studies using Earned Value Management forecasting, it has been argued that the network topology is a driver to indicate the accuracy of these forecasts. However, a new project indicator has been recently defined, i.e. the project regularity, which reflects the value accrue according to the plan. It has shown to outperform the serial/parallel network topology indicator in specifying the accuracy of project forecasts. This paper introduces a novel way to define the project regularity, which provides project managers with an improved indication of the expected forecasting accuracy for their projects. The study is carried out on an empirical database consisting of 100 projects from different sectors, and the results are compared to the academic literature. The experiments show that the new indicator provides a better categorisation compared to the existing approaches. Further, they have shown that the ability of project categorisers to indicate the expected forecasting accuracy is affected by industry sector and project size.
Keywords
Management Science and Operations Research, General Decision Sciences, Project management, Project forecasting, Earned value management, Forecasting accuracy, Empirical database, Project regularity, Earned, duration management, CONSTRUCTION, PERFORMANCE, MANAGEMENT, DURATION

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MLA
Andrade, Paulo André de, et al. “An Empirical Project Forecasting Accuracy Framework Using Project Regularity.” ANNALS OF OPERATIONS RESEARCH, vol. 337, no. 2, 2024, pp. 501–21, doi:10.1007/s10479-023-05269-7.
APA
Andrade, P. A. de, Vanhoucke, M., & Martens, A. (2024). An empirical project forecasting accuracy framework using project regularity. ANNALS OF OPERATIONS RESEARCH, 337(2), 501–521. https://doi.org/10.1007/s10479-023-05269-7
Chicago author-date
Andrade, Paulo André de, Mario Vanhoucke, and Annelies Martens. 2024. “An Empirical Project Forecasting Accuracy Framework Using Project Regularity.” ANNALS OF OPERATIONS RESEARCH 337 (2): 501–21. https://doi.org/10.1007/s10479-023-05269-7.
Chicago author-date (all authors)
Andrade, Paulo André de, Mario Vanhoucke, and Annelies Martens. 2024. “An Empirical Project Forecasting Accuracy Framework Using Project Regularity.” ANNALS OF OPERATIONS RESEARCH 337 (2): 501–521. doi:10.1007/s10479-023-05269-7.
Vancouver
1.
Andrade PA de, Vanhoucke M, Martens A. An empirical project forecasting accuracy framework using project regularity. ANNALS OF OPERATIONS RESEARCH. 2024;337(2):501–21.
IEEE
[1]
P. A. de Andrade, M. Vanhoucke, and A. Martens, “An empirical project forecasting accuracy framework using project regularity,” ANNALS OF OPERATIONS RESEARCH, vol. 337, no. 2, pp. 501–521, 2024.
@article{01HNZD3EBDZTF9BXWTBPZ0JKE4,
  abstract     = {{Forecasting an ongoing project's actual duration is an essential aspect of project management which received considerable attention in the research community. In studies using Earned Value Management forecasting, it has been argued that the network topology is a driver to indicate the accuracy of these forecasts. However, a new project indicator has been recently defined, i.e. the project regularity, which reflects the value accrue according to the plan. It has shown to outperform the serial/parallel network topology indicator in specifying the accuracy of project forecasts. This paper introduces a novel way to define the project regularity, which provides project managers with an improved indication of the expected forecasting accuracy for their projects. The study is carried out on an empirical database consisting of 100 projects from different sectors, and the results are compared to the academic literature. The experiments show that the new indicator provides a better categorisation compared to the existing approaches. Further, they have shown that the ability of project categorisers to indicate the expected forecasting accuracy is affected by industry sector and project size.}},
  author       = {{Andrade, Paulo André de and Vanhoucke, Mario and Martens, Annelies}},
  issn         = {{0254-5330}},
  journal      = {{ANNALS OF OPERATIONS RESEARCH}},
  keywords     = {{Management Science and Operations Research,General Decision Sciences,Project management,Project forecasting,Earned value management,Forecasting accuracy,Empirical database,Project regularity,Earned,duration management,CONSTRUCTION,PERFORMANCE,MANAGEMENT,DURATION}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{501--521}},
  title        = {{An empirical project forecasting accuracy framework using project regularity}},
  url          = {{http://doi.org/10.1007/s10479-023-05269-7}},
  volume       = {{337}},
  year         = {{2024}},
}

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