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A Systematic Review Based on Earned Value Management and Quality

  • Christopher de Souza Lima FranciscoEmail author
  • Adler Diniz de Souza
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 800)

Abstract

Currently the Project Management Institute (PMI) estimates that approximately 25% of the world’s Gross Domestic Product (GDP) is spent on projects of various kinds and that about 16.5 million professionals are directly involved in project management worldwide. This volume of projects and changes in the world scenario, increasingly competitive, generate the need for faster results, with higher quality, lower costs and shorter deadlines. Among the main techniques for analyzing cost, time and scope performance, the Earned Value Management (EVM) technique is considered to be the most reliable. Several formulas derived from EVM’s measurements are available and have been studied over the past 15 years. However, EVM has a significant limitation regarding quality in its method. The technique is effective in providing cost and schedule related information but is still weak in taking the quality factor into account. The main objective of this work is to contribute to studies that seek to add the quality component into EVM and comparing performance between them. This paper presents the results of a systematic review, providing a comprehensive summary of the main problems with the use of the EVM technique and the possible solutions found to improve its capacity to predict the impact of quality (possible bugs or nonconformities) in the course of a project’s life cycle.

References

  1. 1.
    Lipke, W.: Project duration forecasting…a comparison of earned value management methods to earned schedule. Meas. News 21(01), 24–31 (2008)Google Scholar
  2. 2.
    Lipke, W.: Statistical methods applied to EVM: the next frontier. CrossTalk 19, 20–23 (2006)Google Scholar
  3. 3.
    Lipke, W., Zwikael, O., Henderson, K., Anbari, F.: Prediction of project outcome. Int. J. Proj. Manag. 27(4), 400–407 (2009)CrossRefGoogle Scholar
  4. 4.
    Solomon, P.J.: Performance-based earned value. In: INCOSE International Symposium, vol. 15 (2007)Google Scholar
  5. 5.
    Leu, S.-S., Lin, Y.-C., Chen, T.-A., Ho, Y.-Y.: Improving traditional earned value management by incorporating statistical process charts. In: 23rd International Symposium on Automation and Robotics in Construction (2006)Google Scholar
  6. 6.
    Yerabolu, R., Institute, P.M.: Framework for Integrating Project Quality, Risk Management, and Integration Management Disciplines Into Earned Value Management (EVM) for Deriving Performance Based Earned Value (PBEV) (2010), pp. 275–279. Tokyo, Japan (2006)Google Scholar
  7. 7.
    Ma, X., Yang, B.: Optimization study of earned value method in construction project management. In: 2012 International Conference on Information Management, Innovation Management and Industrial Engineering, vol. 2, pp. 201–204 (2012)Google Scholar
  8. 8.
    Solomon, P.: Using cmmi to improve earned value management. Technical Report CMU/SEI-2002-TN-016, Software Engineering Institute, Carnegie Mellon University, Pittsburgh (2002)Google Scholar
  9. 9.
    Lipke, W.: Schedule is different. PMI CPM J. Meas. News. 1, 31–34 (2003).Google Scholar
  10. 10.
    Dodson, M., Defavari, G., de Carvalho, V.: Quality: the third element of earned value management. Proc. Comput. Sci. 64, 932–939 (2015), Conference on ENTERprise Information Systems/International Conference on Project MANagement/Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 7–9 Oct (2015)CrossRefGoogle Scholar
  11. 11.
    Siddiqui, S., Ullah, F., Thaheem, M.J, Gabriel, H.: Six sigma in construction: a review of critical success factors. 7, 06 (2016)Google Scholar
  12. 12.
    Thomas, G., Fernández, W.: Success in it projects: a matter of definition? Int. J. Proj. Manag. 26(7), 733–742 (2008) Special Issue: Achieving IT Project SuccessGoogle Scholar
  13. 13.
    Baccarini, D.: The Logical Framework Method for Defining Project Success. Project Management Institute, Newtown Square (1999)CrossRefGoogle Scholar
  14. 14.
    Ika, L.A.: Project success as a topic in project management journals. Proj. Manag. J. 40(4), 6–19 (2009)CrossRefGoogle Scholar
  15. 15.
    Solomon, P.J.: Pratical perfomance-based earned value. In: Systems and Software Technology Conference (2006)Google Scholar
  16. 16.
    DeMarco, T.: Controlling Software Projects: Management, Measurement, and Estimates. Yourdon Press, New York (1982)Google Scholar
  17. 17.
    Khalid, T.A.: Controlling software cost using fuzzy quality based EVM. In: International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (2015)Google Scholar
  18. 18.
    de Souza, A.D., Rocha, A.R.C., Cristina, D., Constantino, B.A.: A proposal for the improvement of project’s cost predictability using earned value management and quality data – an empirical study, pp. 170–181. Springer, Berlin/Heidelberg (2014)Google Scholar
  19. 19.
    Salari, M., Bagherpour, M., Reihani, M.: A time -cost trade-off model by incorporating fuzzy earned value management: a statistical based approach. J. Intell. Fuzzy Syst. 28, 11 (2014)Google Scholar
  20. 20.
    Iranmanesh, S.H., Hojati, Z.T.: Intelligent systems in project performance measurement and evaluation, pp. 581–619. Springer, Cham (2015)CrossRefGoogle Scholar
  21. 21.
    Lipke, W.: Is something missing from project management? CrossTalk 26, 16–20 (2013)Google Scholar
  22. 22.
    de Souza, A.D., Rocha, A.R.C.: A Proposal for the Improvement Predictability of Cost Using Earned Value Management and Quality Data, pp. 190–201. Springer, Berlin/Heidelberg (2013)Google Scholar
  23. 23.
    Solomon1, P.J.: Basing earned value on technical performance. CrossTalk 26, 25–28 (2013)Google Scholar
  24. 24.
    Naeni, L.M, Shadrokh, S., Salehipour, A.: A fuzzy approach for the earned value management. Int. J. Proj. Manag. 29(6), 764–772 (2011)CrossRefGoogle Scholar
  25. 25.
    Putnam, L.H., Myers, W.: Five Core Metrics: Intelligence Behind Successful Software Management. Dorset House Publishing Co., Inc., New York (2003)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Christopher de Souza Lima Francisco
    • 1
    Email author
  • Adler Diniz de Souza
    • 1
  1. 1.Federal University of ItajubáItajubáBrazil

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