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Using the ProdFlow(TM) approach to address the myth of productivity in r&d organizations
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Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement table of contents
Kaiserslautern, Germany
SESSION: Experience in process improvement table of contents
Pages 339-341  
Year of Publication: 2008
ISBN:978-1-59593-971-5
Authors
Melanie Ruhe  Siemens AG, Munich, Germany
Stefan Wagner  Technische Universität München, Garching, Germany
Sponsors
SIGSOFT: ACM Special Interest Group on Software Engineering
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Software productivity has been analyzed traditionally in terms of size measures such as LOC or FP. These measures have failed to provide a comprehensive basis for productivity analysis. In the research department of the Siemens AG the new approach ProdFLOW™ for the analysis and management of a research & development organization's productivity is being created based on a revised understanding of the term productivity. Former studies often start with fixed, typical indicators and quantitatively analyze the relation between productivity and the indicator by regression models. ProdFLOW™ departs from the fixed model approach, which might not fit to the conditions of the organization. Instead an organization-specific model based on the substantial levers of the productivity, which are both influenceable and measurable, are compiled together with the experts of the organization. The paper explains the new approach as well as gives an example to illustrate our approach based on the results of three performed case studies.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
B. Boehm et. al. Value-Based Software Engineering. Springer-Verlag 2005
 
2
T. Little, Value Creation and Capture, IEEE Software 2004
 
3
 
4
N. Fenton. Managing Risk in the Modern World, Application of Bayesian Networks
 
5
P. Aisenbrey. Deductive Empirical Social Research Based on the Non-Classic Theory of Self-Monitoring. PhD thesis. FU Berlin, 2007
 
6
Stamelos et. al. On the use of Bayesian belief networks for the prediction of software productivity, Information and Software Technology, Vol. 45 (2003), pp. 51--6

Collaborative Colleagues:
Melanie Ruhe: colleagues
Stefan Wagner: colleagues