The ASCCR Frame for Learning Essential Collaboration Skills

Abstract

Abstract Statistics and data science are especially collaborative disciplines that typically require practitioners to interact with many different people or groups. Consequently, interdisciplinary collaboration skills are part of the personal and professional skills essential for success as an applied statistician or data scientist. These skills are learnable and teachable, and learning and improving collaboration skills provides a way to enhance one’s practice of statistics and data science. To help individuals learn these skills and organizations to teach them, we have developed a framework covering five essential components of statistical collaboration: Attitude, Structure, Content, Communication, and Relationship. We call this the ASCCR Frame. This framework can be incorporated into formal training programs in the classroom or on the job and can also be used by individuals through self-study. We show how this framework can be applied specifically to statisticians and data scientists to improve their collaboration skills and their interdisciplinary impact. We believe that the ASCCR Frame can help organize and stimulate research and teaching in interdisciplinary collaboration and call on individuals and organizations to begin generating evidence regarding its effectiveness.