This paper outlines a four step effort estimation study and focuses on the first and second step. The four steps are formulated to successively introduce a more formal effort experience base. The objective of the study is to evaluate the needed formalism to improve effort estimation and to study different approaches to record and reuse experiences from effort planning in software projects. In the first step (including seven projects), the objective is to compare estimation of effort based on a rough figure (indicating approximate size of the projects) with an informal experience base. The objective of the second step is on reuse of experiences from an effort experience base, where the outcomes of seven previous projects were stored. Seven new projects are planned based on the previous experiences. The plans are, after project completion, compared with the initial plans and with the data from six out of the seven new projects, to plan the seventh. It is clear from the studies that effort estimation is difficult and that the mean estimation error is in the range of 14%-19% independent of the approach used. Further, it is concluded that the best estimates are obtained when the projects use the previous experience and complement this information with their own thoughts and opinions. Finally, it is concluded that data collection is not enough in itself, the data collected must be processed, i.e. interpreted, generalized and synthesized into a reusable form.
- Datavetenskap (datalogi)