Statistical analysis for comparison of overall performance of projects using Weibull analysis on earned value metrics

Most organizations have evaluated project performance primarily through cost and schedule performance measures, such as earned value management, for projects. However, to date, few tools in the project management literature have been proposed for enabling comparisons of the overall performance of projects. This study introduces a simple index, the critical ratio in time (CR(t)), as a measure of the overall performance of a project. The index can be easily calculated on the basis of the earned value (EV) data, which are normally available from a project cost system. Based on the index, a statistical analysis for the comparison of the overall performance of projects using Weibull analysis on EV metrics is proposed. The statistical analysis can be performed on a spreadsheet, such as Microsoft® Excel®. Furthermore, the detailed steps in the analysis are discussed along with an example in which five sample projects are analyzed and compared. Based on the obtained results, the author concludes that the proposed approach on the basis of CR(t) data can provide a robust and effective method for managers to evaluate and compare the overall performance of projects, and can be applicable in evaluating the project whose value has been determined (e.g. contracted projects).

[1]  Gad Vitner,et al.  MPCS: Multidimensional Project Control System , 2004 .

[2]  David S. Wilson,et al.  Assessing the performance of construction projects: Implementing earned value management at the General Services Administration , 2005 .

[3]  Quentin W. Fleming,et al.  Earned Value Project Management , 1996 .

[4]  Robert B. Abernethy,et al.  The new Weibull handbook , 1993 .

[5]  J. H. Sheesley.  Methods for Statistical Analysis of Reliability and Life Data , 1977 .

[6]  Mario Vanhoucke,et al.  A comparison of different project duration forecasting methods using earned value metrics , 2006 .

[7]  Daniel M. Brandon.  Implementing Earned Value Easily and Effectively , 1998 .

[8]  E. Kay,et al.  Methods for statistical analysis of reliability and life data , 1974 .

[9]  Jennifer A. Farris,et al.  Evaluating the Relative Performance of Engineering Design Projects: A Case Study Using Data Envelopment Analysis , 2006, IEEE Transactions on Engineering Management.

[10]  Major David S. Christensen.  Using Performance Indices to Evaluate the Estimate at Completion , 1994 .

[11]  Paul Solomon,et al.  Appendix C-1: Excerpts from NDIA PMSC ANSI/EIA 748-A, Standard for Earned Value Management Systems Intent Guide , 2006 .

[12]  Sigmund J. Amster,et al.  The Statistical Treatment of Fatigue Experiments , 1964 .

[13]  Kam Judgev.  Project management: the managerial process , 2010 .

[14]  N. Singpurwalla,et al.  Methods for Statistical Analysis of Reliability and Life Data. , 1975 .

[15]  W. Duncan.  A GUIDE TO THE PROJECT MANAGEMENT BODY OF KNOWLEDGE , 1996 .

[16]  Ray R. Venkataraman,et al.  Cost and Value Management in Projects , 2008 .

[17]  Jack R. Meredith,et al.  Project Management: A Managerial Approach , 1989 .

[18]  Hiromitsu Kumamoto,et al.  Probabilistic Risk Assessment and Management for Engineers and Scientists , 1996 .

[19]  Kym Henderson.  Earned Schedule: A Breakthrough Extension to Earned Value Management , 2007 .

[20]  Mario Vanhoucke,et al.  Measuring the accuracy of earned value/earned schedule forecasting predictors , 2007 .

[21]  Khaled Nassar,et al.  Using Weibull Analysis for Evaluation of Cost and Schedule Performance , 2005 .

[22]  Glenn Ballard,et al.  EARNED VALUE METHOD AND CUSTOMER EARNED VALUE , 2002 .

[23]  Gad Vitner,et al.  Using data envelope analysis to compare project efficiency in a multi-project environment , 2006 .

[24]  C. Plaisant,et al.  Project Portfolio Earned Value Management Using Treemaps , 2004 .

[25]  Andrew S. Chang.  Defining Cost/Schedule Performance Indices and Their Ranges for Design Projects , 2001 .