A Multivariate Analysis Technique to Support Guidelines for Team Size in Digital Projects

The design of increasingly complex digital systems requires teamwork. The size and composition of teams are critical for initial activities focused on understanding the problems to be addressed through digital technology. Regardless of the adopted methodology, from the classic waterfall to the agile approach, the first step is to identify the needs and objectives – requirements in software engineering terms – of the various stakeholders. Requirements elicitation is key to the success of digital projects and requires a multidisciplinary approach. A relevant question then is that of the ideal size of teams working in requirements elicitation sessions. The existing literature provides guidelines, but they are usually not supported by empirical data. A recent survey has partially filled this gap by providing data on the issue of team size. Thanks to the availability of that data, this paper proposes applying the multiple correspondence analysis (MCA), to further exploit them. MCA allows multiple factors to be considered simultaneously, and above all it does not require ex-ante assumptions to be made about the associations between them. MCA, which is not well known in software engineering, makes it possible to identify and graphically visualize relationships between many variables. The ultimate goal is to eventually use the identified profiles to support the guidelines for team staffing. Due to the size of the dataset (92 responses), the results of the MCA are exploratory. Nevertheless, they confirm mainstream guidelines.