Team leadership is about how a team learns to lead itself. It is not about who is the leader of the team, but the process of building confidence and leadership acumen in all members of the team. This includes skill building but is not about skills per se. It involves competencies, both core technical competence and interpersonal and cultural competence.
I learned some tough lessons about how (not) to lead and collaborate as associate chair and later chair of the Statistics Department. I played a major role in transforming the department’s mission (see Data, Models and Statistics), which enabled substantial expansion of academic staff and fostered development of multiple innovative degree programs. However, I fell short in team-building and getting broad “buy-in” from faculty. During that time, I began taking various leadership trainings, which led later to coaching as I founded the Data Science Institute (DSI). I have made many mistakes along my journey, fertile ground for substantial personal and professional growth.
My teams as case studies
The slide decks below illustrate my experiences leading and being in teams. Each team member has multiple roles and perspectives, which influence their path toward multiple competencies. Data Rich Story Telling speaks broadly to the creative process of telling stories with data. Stats Collaboration addresses the multiple roles that arise when team-building with scientific colleagues. Quantitative Trait Loci (QTLs) have been a prominent part of my research collaborations, blending teams of biologists from multiple fields (agronomy, biochemistry, genetics) with data scientists focused on systems genetics. As DSI Founding Director, I oversaw multiple teams to first create and build the center, and later collaborate with other teams to address the Covid-19 pandemic. Recently, I have been teaming up with UW Earth Partnership and NSF’s ESIIL on Indigenous pathways to environmental data science.