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Issue No. 05 - May (2003 vol. 29)
ISSN: 0098-5589
pp: 398-416
<p><b>Abstract</b>—Learning from high performance projects is crucial for software process improvement. Therefore, we need to identify outstanding projects that may serve as role models. It is common to measure productivity as an indicator of performance. It is vital that productivity measurements deal correctly with variable returns to scale and multivariate data. Software projects generally exhibit variable returns to scale, and the output from ERP projects is multivariate. We propose to use Data Envelopment Analysis Variable Returns to Scale (DEA VRS) to measure the productivity of software projects. DEA VRS fulfills the two requirements stated above. The results from this empirical study of 30 ERP projects extracted from a benchmarking database in Accenture identified six projects as potential role models. These projects deserve to be studied and probably copied as part of a software process improvement initiative. The results also suggest that there is a 50 percent potential for productivity improvement, on average. Finally, the results support the assumption of variable returns to scale in ERP projects. We recommend DEA VRS be used as the default technique for appropriate productivity comparisons of individual software projects. Used together with methods for hypothesis testing, DEA VRS is also a useful technique for assessing the effect of alleged process improvements.</p>
Software process improvement, benchmarking, best practice identification, software project management, multivariate productivity measurements, data envelopment analysis (DEA), software development, enterprise resource planning (ERP), software metrics, economies of scale, variable returns to scale.

E. Stensrud and I. Myrtveit, "Identifying High Performance ERP Projects," in IEEE Transactions on Software Engineering, vol. 29, no. , pp. 398-416, 2003.
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