After nearly five years serving as the City and County of San Francisco’s first chief data officer, Joy Bonaguro has moved on.
First announced by her coworker, Data Services Manager Jason Lally, in a blog post Monday, Bonaguro’s departure highlights the influence a single technology leader can have on an organization. To hear Lally tell it, San Francisco has lost not only the top official in his office, DataSF , but a veritable talent.
“I was immediately struck by her optimism, warmth, strategic action, grit and determination to move things forward,” Lally writes. “When offered the opportunity to become her first hire, it was not a hard decision to join her and double the team.”
Among Bonaguro’s accomplishments, Lally calls out the cultural changes she incited.
“Joy brought on the brightest people I’ve had the opportunity to work with,” Lally said. “She allowed us to contribute not just our skills but our ideas to shape DataSF. She is an empowering leader that put her heart into the team as well as the work.”
Diligence and a tendency toward strategic thinking are common traits for those who work in data, and Bonaguro’s organizational awareness and attention to detail come through clearly in her interviews.
When recognized as one of StateScoop’s 2018 Top Women in Tech , she underscored the importance of exerting what she called “artful assertiveness.” She also denounced simplistic truisms about “finding your passion” in favor of more substantive advice. One piece of that insight: “People don’t do what they don’t own.”
Bonaguro drew her approach from experience as an IT policy manager at the Lawrence Berkeley National Laboratory and in data and design roles at the Greater New Orleans Community Data Center before heading to San Francisco in February 2014.
Interviewed for a report published by the Harvard Kennedy School’s Ash Center for Democratic Governance, Bonaguro advocated for a characteristically subtle approach, rather than adopting the top-down mandates issued by some leaders.
“Shaking your fist and indicting departments for data work won’t endear you to anyone. Instead, take the time to understand their perspective, their priorities, and their challenges and problems,” Bonaguro said. “Then help them identify ways data can help.”
She told StateScoop earlier this year she was proud of the work she was doing at the city with her team and Lally, naming two recent service offerings: dashboarding self-service and a data science service.
“Our core services, open data, dashboarding, and data science reinforce one another,” Bonaguro explained. “For example, we help a department publish data and build a dashboard on top. That dashboard then generates questions that turn into a data science project (or vice versa). All of our work is then reinforced and codified through our Data Academy trainings.”
The Data Academy, a partnership between the city’s data division and the Controller’s Office to provide internal data training, is credited with saving San Francisco as much as $6 million annually through savings in staff time. The academy is one of a host of initiatives delivered by Bonaguro’s office during her time at the city.
In his blog post, Lally names the city’s open data initiative, data science initiative, and What Works Cities certification as key advancements in the city’s data projects during her time in local government.
Lally focuses on the quantitative improvements Bonaguro brought to the city. He reports a 55 percent growth in sessions on the city’s open data portal over the last year and a 37 percent increase in users’ downloading of data. A partnership with the Office of the Assessor-Recorder reduced a backlog of more than 250 assessments and increasing time to revenue on $407 million.
But between reveling in the numbers, Lally says Bonaguro’s impact “will not be forgotten.”
“And while goodbyes are hard, I am also excited for the next chapter leading DataSF,” Lally writes. “One of the greatest influences Joy had on me and our team is that she equipped us to make informed choices; to not feel boxed in by prior decisions. In that spirit, we will continuously improve and iterate on DataSF.”