How Valuable is company-specific Data Compared to multi-company Data for Software Cost Estimation?

The objective of this paper is to investigate the pertinent question whether multi-organizational data is valuable for software project cost estimation. Local, company-specific data is widely believed to provide a better basis for accurate estimates. On the other hand, multi-organizational databases provide an opportunity for fast data accumulation and shared information benefits. Therefore, this paper trades off the potential advantages and drawbacks of using local data as compared to multi-organizational data. Motivated by the results from previous investigations, we further analyzed a large cost database from Finland that collects standard cost factors and includes information on six individual companies. Each of these companies provided data for more than ten projects. This information was used to compare the accuracy between company-specific (local) and company-external (global) cost models. Consistent with some of the previous investigations in this area, the general trends in the results are surprising. They show that company-specific models seem not to yield better results than the companyexternal models. Our results are based on applying two standard statistical estimation methods (OLS-regression, Analysis of Variance) and Analogy-based estimation.