Managing Team Performance in Product Development: A Data-Driven Case Study

This thesis investigates how demographic, organisational, and work-process variables influence team performance outcomes in software product development. Building on performance management theory and business statistics, the study analyses key performance indicators at team level (Velocity and Time Allocation) and individual micro-level metrics (Reliability). The empirical analysis is based on operational data retrieved from Doxee S.p.A, these data were collected across multiple sprints and aggregated into semester-level observations. Descriptive and Inferential Statistical methods are used to translate raw performance data into useful managerial insights. Findings show greater involvement in support activities is consistently associated with lower development capacity. Teams with a more balanced mixes of roles and seniority display steadier velocity trends. Individual reliability improves in the second semester increasing accuracy in personal planning. Finally, demographic and organizational composition contributes to maintaining consistent performance patterns. Overall, the results provide actionable guidance for managers seeking to refine KPI system, structure teams effectively and strengthened data drive decision making in product development environments.