Journal article
Prediction of project outcome The application of statistical methods to earned value management and earned schedule performance indexes
International journal of project management, v 27(4), pp 400-407
01 May 2009
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Earned value management (EVM) has provided methods for predicting the final cost for projects. In large part, these methods have not been improved upon since their beginnings and, with one exception, remain unsubstantiated as to accuracy. At the present time, EVM application guidance does not support prediction of final duration for the schedule component of projects.
The objective of this research is to improve the capability of project managers for making informed decisions by providing a reliable forecasting method of the final cost and duration. The method put forth and its evaluation make use of a well established project management method, a recent technique for analyzing schedule performance, and the mathematics of statistics to achieve its purpose-EVM, earned schedule (ES) and statistical prediction and testing methods.
The calculation method proposed was studied using data from 12 projects. The results for both final cost and duration are shown to be sufficiently reliable for general application of the forecasting method. The use of the method is encouraged; it may be applied irrespective of the type of work or cost and duration magnitude of the project. (C) 2008 Elsevier Ltd and IPMA. All rights reserved.
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Details
- Title
- Prediction of project outcome The application of statistical methods to earned value management and earned schedule performance indexes
- Creators
- Walt Lipke - Chapter Arts CentreOfer Zwikael - Victoria University of WellingtonKym HendersonFrank Anbari - George Washington University
- Publication Details
- International journal of project management, v 27(4), pp 400-407
- Publisher
- Elsevier
- Number of pages
- 8
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Richard C. Goodwin College of Professional Studies
- Web of Science ID
- WOS:000266046200010
- Scopus ID
- 2-s2.0-64449085007
- Other Identifier
- 991021861641504721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Management