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A lognormal approximation of activity duration in PERT using two time estimates

Author

Listed:
  • S Mohan

    (Arizona State University)

  • M Gopalakrishnan

    (Arizona State University)

  • H Balasubramanian

    (Arizona State University)

  • A Chandrashekar

    (AXP Project Center of Excellence, IBM Corporation)

Abstract

The success behind effective project management lies in estimating the time for individual activities. In many cases, these activity times are non-deterministic. In such situations, the conventional method (project evaluation and review technique (PERT)) obtains three time estimates, which are then used to calculate the expected time. In practice, it is often difficult to get three accurate time estimates. A recent paper suggests using just two time estimates and an approximation of the normal distribution to obtain the expected time and variance for that activity. In this paper, we propose an alternate method that uses only two bits of information: the most-likely and either the optimistic or the pessimistic time. We use a lognormal approximation and experimental results to show that our method is not only better than the normal approximation, but also better than the conventional method when the underlying activity distributions are moderately or heavily right skewed.

Suggested Citation

  • S Mohan & M Gopalakrishnan & H Balasubramanian & A Chandrashekar, 2007. "A lognormal approximation of activity duration in PERT using two time estimates," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 827-831, June.
    • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:6:d:10.1057_palgrave.jors.2602204
    DOI: 10.1057/palgrave.jors.2602204
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    References listed on IDEAS

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    1. D Johnson, 2002. "Triangular approximations for continuous random variables in risk analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 457-467, April.
    2. Donald L. Keefer & William A. Verdini, 1993. "Better Estimation of PERT Activity Time Parameters," Management Science, INFORMS, vol. 39(9), pages 1086-1091, September.
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    Cited by:

    1. Trietsch, Dan & Mazmanyan, Lilit & Gevorgyan, Lilit & Baker, Kenneth R., 2012. "Modeling activity times by the Parkinson distribution with a lognormal core: Theory and validation," European Journal of Operational Research, Elsevier, vol. 216(2), pages 386-396.
    2. Colin, Jeroen & Vanhoucke, Mario, 2014. "Setting tolerance limits for statistical project control using earned value management," Omega, Elsevier, vol. 49(C), pages 107-122.
    3. Pérez, José García & Martín, María del Mar López & García, Catalina García & Sánchez Granero, Miguel Ángel, 2016. "Project management under uncertainty beyond beta: The generalized bicubic distribution," Operations Research Perspectives, Elsevier, vol. 3(C), pages 67-76.
    4. Hajdu M. & Isaac S., 2016. "Sixty years of project planning: history and future," Organization, Technology and Management in Construction, Sciendo, vol. 8(1), pages 1499-1510, December.
    5. Catalina García & José Pérez & Salvador Rambaud, 2010. "Proposal of a new distribution in PERT methodology," Annals of Operations Research, Springer, vol. 181(1), pages 515-538, December.
    6. Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo & Newman, Alexandra, 2024. "A target-time-windows technique for project scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 314(2), pages 792-806.

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