Customized predictive models for process improvement projects

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. © 2008 Springer-Verlag Berlin Heidelberg.