  Managing software development productivity and effort are key issues in
software organizations. Identifying the most relevant factors influencing
project performance is essential for implementing business strategies by
selecting and adjusting proper improvement activities. There is, however, a
large number of potential influencing factors. This paper proposes a novel
approach for identifying the most relevant factors influencing software
development productivity. The method elicits relevant factors by integrating
data analysis and expert judgment approaches by means of a multi-criteria
decision support technique. Empirical evaluation of the method in an industrial
context has indicated that it delivers a different set of factors compared to
individual data- and expert-based factor selection methods. Moreover,
application of the integrated method significantly improves the performance of
effort estimation in terms of accuracy and precision. Finally, the study did
not replicate the observation of similar investigations regarding improved
estimation performance on the factor sets reduced by a data-based selection
method.
