Project regularity: Development and evaluation of a new project characteristic

Jordy Batselier , Mario Vanhoucke

Journal of Systems Science and Systems Engineering ›› 2017, Vol. 26 ›› Issue (1) : 100 -120.

PDF
Journal of Systems Science and Systems Engineering ›› 2017, Vol. 26 ›› Issue (1) : 100 -120. DOI: 10.1007/s11518-016-5312-6
Article

Project regularity: Development and evaluation of a new project characteristic

Author information +
History +
PDF

Abstract

The ability to accurately characterize projects is essential to good project management. Therefore, a novel project characteristic is developed that reflects the value accrue within a project. This characteristic, called project regularity, is expressed in terms of the newly introduced regular/irregular-indicator RI. The widely accepted management system of earned value management (EVM) forms the basis for evaluation of the new characteristic. More concretely, the influence of project regularity on EVM forecasting accuracy is assessed, and is shown to be significant for both time and cost forecasting. Moreover, this effect appears to be stronger than that of the widely used characteristic of project seriality expressed by the serial/parallel-indicator SP. Therefore, project regularity could also be useful as an input parameter for project network generators. Furthermore, the introduction of project regularity can provide project managers with a more accurate indication of the time and cost forecasting accuracy that is to be expected for a certain project and, correspondingly, of how a project should be built up in order to obtain more reliable forecasts during project control.

Keywords

Project management / earned value management / time and cost forecasting / empirical database / Monte Carlo simulation / project control system

Cite this article

Download citation ▾
Jordy Batselier, Mario Vanhoucke. Project regularity: Development and evaluation of a new project characteristic. Journal of Systems Science and Systems Engineering, 2017, 26(1): 100-120 DOI:10.1007/s11518-016-5312-6

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Agrawal M., Elmaghraby S., Herroelen W.. DAGEN: a generator of testsets for project activity nets. European Journal of Operational Research, 1996, 90: 376-382.

[2]

Anbari F.. Earned value project management method and extensions. Project Management Journal, 2003, 34: 12-23.

[3]

Batselier J., Vanhoucke M.. Construction and evaluation framework for a real-life project database. International Journal of Project Management, 2015, 33: 697-710.

[4]

Batselier J., Vanhoucke M.. Empirical evaluation of earned value management forecasting accuracy for time and cost. Journal of Construction Engineering and Management, 2015, 141: 05015010.

[5]

Christensen D.. The costs and benefits of the earned value management process. Acquisition Review Quarterly, Fall, 1998 373-386.

[6]

Cioffi D.. A tool for managing projects: an analytic parameterization of the S-curve. International Journal of Project Management, 2005, 23: 215-222.

[7]

Cioffi D.. Completing projects according to plans: an earned-value improvement index. Journal of the Operational Research Society, 2006, 57: 290-295.

[8]

Demeulemeester E., Vanhoucke M., Herroelen W.. RanGen: a random network generator for activity-on-the-node networks. Journal of Scheduling, 2003, 6: 17-38.

[9]

Egnot J.. Earned progress management-a unified theory of earned value & earned schedule concepts. The Measurable News, Issue, 2011, 4: 8-24.

[10]

Elshaer R.. Impact of sensitivity information on the prediction of project’s duration using earned schedule method. International Journal of Project Management, 2012, 31: 579-588.

[11]

Fleming Q., Koppelman J.. Earned Value Project Management, 2010

[12]

Hall N.. Project management: recent developments and research opportunities. Journal of Systems Science and Systems Engineering, 2012, 21: 129-143.

[13]

Henderson K.. Earned schedule: a breakthrough extension to earned value management. PMI Asia Pacific Global Congress Proceedings, 2007

[14]

Jacob D., Kane M.. Forecasting schedule completion using earned value metrics revisited. The Measurable News, Summer, 2004, 1: 11-17.

[15]

Kao E., Queyranne M.. On dynamic programming methods for assembly line balancing. Operations Research, 1982, 30: 375-390.

[16]

Kim E., Wells W., Duffey M.. A model for effective implementation of earned value management methodology. International Journal of Project Management, 2003, 21: 375-382.

[17]

Kolisch R., Sprecher A., Drexl A.. Characterization and generation of a general class of resource-constrained project scheduling problems. Management Science, 1995, 41: 1693-1703.

[18]

Lipke W.. Schedule is different. The Measurable News, Summer, 2003 31-34.

[19]

Marshall R.. The contribution of earned value management to project success on contracted efforts. Journal of Contract Management, 2007 21-33.

[20]

Mastor A.. An experimental and comparative evaluation of production line balancing techniques. Management Science, 1970, 16: 728-746.

[21]

Meredith J., Mantel S.. Project Management: A Managerial Approach, 2003, New York: Wiley

[22]

PMI A Guide to the Project Management Body of Knowledge, 2008, Newtown Square, Pennsylvania: Project Management Institute

[23]

Rujirayanyong T.. A comparison of three completion date predicting methods for construction projects. Journal of Research in Engineering and Technology, 2009, 6: 305-318.

[24]

Schwindt C.. A new problem generator for different resource-constrained project scheduling problems with minimal and maximal time lags, 1995

[25]

Tavares L.. Advanced Models for Project Management, 1999, Dordrecht: Kluwer Academic Publishers.

[26]

Tavares L., Ferreira J., Coelho J.. The risk of delay of a project in terms of the morphology of its network. European Journal of Operational Research, 1999, 119: 510-537.

[27]

Van De Velde R.. Time is up: assessing schedule performance with earned value. PM World Today, 2007, 9: 1-10.

[28]

Vandevoorde S., Vanhoucke M.. A comparison of different project duration forecasting methods using earned value metrics. International Journal of Project Management, 2006, 24: 289-302.

[29]

Vanhoucke M.. Measuring time-improving project performance using earned value management, 2010.

[30]

Vanhoucke M.. Using activity sensitivity and network topology information to monitor project time performance. Omega-The International Journal of Management Science, 2010, 38: 359-370.

[31]

Vanhoucke M.. On the dynamic use of project performance and schedule risk information during project tracking. Omega-The International Journal of Management Science, 2011, 39: 416-426.

[32]

Vanhoucke M.. Measuring the efficiency of project control using fictitious and empirical project data. International Journal of Project Management, 2012, 30: 252-263.

[33]

Vanhoucke M.. Project Management with Dynamic Scheduling: Baseline Scheduling, Risk Analysis and Project Control, 2012.

[34]

Vanhoucke M.. Integrated project management and control: first comes the theory, then the practice, 2014.

[35]

Vanhoucke M., Coelho J., Debels D., Maenhout B., Tavares L.. An evaluation of the adequacy of project network generators with systematically sampled networks. European Journal of Operational Research, 2008, 187: 511-524.

[36]

Vanhoucke M., Vandevoorde S.. A simulation and evaluation of earned value metrics to forecast the project duration. Journal of the Operational Research Society, 2007, 58: 1361-1374.

AI Summary AI Mindmap
PDF

472

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/