A Systematic Review of Studies Comparing Estimation Accuracy between Cross-company and Within-company Effort Models

Emilia Mendes (Univ of Auckland, NZ)

OBJECTIVE – The objective of this talk is to present our findings regarding under what circumstances individual organisations would be able to rely on cross-company based estimation models.

METHOD – We performed a systematic review of studies that compared predictions from cross-company models with predictions from within-company models based on analysis of project data.

RESULTS – Ten papers compared cross-company and within-company estimation models, however, only seven of the papers presented independent results. Of those seven, three found that cross-company models were as good as within-company models, four found cross-company models were significantly worse than within-company models. Experimental procedures used by the studies differed making it impossible to undertake formal meta-analysis of the results. The main trend distinguishing study results was that studies with small single company data sets (i.e. <20 projects) that used leave-one-out cross-validation all found that the within-company model was significantly more accurate than the cross-company model.

CONCLUSIONS – The results of our systematic review are inconclusive. It is clear that some organisations would be ill-served by cross-company models whereas others would benefit. Further studies are needed, but they must be independent (i.e. based on different data bases or at least different single company data sets) and should address specific hypotheses looking at the conditions that would favour cross-company or within-company models. In addition, experimenters need to standardise their experimental procedures to enable formal meta-analysis.