Customized Predictive Models for Process Improvement Projects

Authors:
Thomas Birkhölzer;Christoph Dickmann;Harald Klein;Jürgen Vaupel;Stefan Ast;Ludger Meyer
Affiliations:
University of Applied Sciences Konstanz, Konstanz, Germany 78462;Siemens Medical Solutions, Erlangen, Germany 91050;Siemens CT SE 3, München, Germany 81730;Siemens Medical Solutions, Erlangen, Germany 91050;Siemens CT SE 3, München, Germany 81730;Siemens CT SE 3, München, Germany 81730
Venue:
PROFES '08 Proceedings of the 9th international conference on Product-Focused Software Process Improvement
Year:
2008

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Abstract

A methodology is presented to quantitatively model the expected relationships between investments in process improvements and improvements in business measures. Such a predictive model can be used as an auxiliary in process improvement planning in addition to established models like CMMI. Different from a generic model like CMMI, the proposed methodology allows for creating a fully customized model focusing on the context or product at hand. To manage the inherent parameter uncertainty of quantitative modelling of software processes a novel approach in this context is used by explicitly handling the parameter variations using interval arithmetic. The paper outlines the methodology and presents results from a study at Siemens.