While data science teams do not yet typically use a standard team process methodology, researchers are starting to explore process methodologies that improve team performance. However, little has been done to understand what might be the key acceptance factors for teams to implement a data science process methodology. To address this gap, the Diffusion of Innovation Theory is used as a theoretical lens to identify factors that might drive an organization to adopt a data science process methodology. The results of this qualitative research effort found ten factors that can influence a team to use, or not use, a data science process methodology. In short, eight positive factors were found with respect to relative advantage and compatibility and two negative factors were identified with respect to complexity. While more work is required to validate and refine these factors, the derived acceptance model can help teams as they consider adopting an improved data science process methodology.
saltz, jeff, "Identifying the Key Drivers for Teams to Use a Data Science Process Methodology" (2018). Research-in-Progress Papers. 58.