Guest: Jessica Lachs - VP of Analytics and Data Science at DoorDash. Jessica has been with DoorDash for over 10 years, helping build one of the most impactful data teams in tech. She was the first GM at DoorDash and previously founded GiftSimple. Key Takeaways: Centralized Data Teams: Jessica advocates for a centralized data team model, which ensures consistent talent standards, growth opportunities, and uniform methodologies across the organization. Proactive Analytics: Data teams should not just answer questions but also identify opportunities and provide actionable insights. Carving out time for exploratory work is crucial. Simple Metrics: Avoid complex composite metrics. Instead, choose simple, understandable metrics that align short-term actions with long-term outcomes. Focus on Edge Cases: Pay attention to rare but impactful negative experiences, like 'Never Delivered' orders, to improve overall service quality and reduce churn. Diverse Backgrounds: Hiring people from various backgrounds, including non-traditional data roles, can enrich the team and bring new perspectives. Topics Covered: Centralized vs. embedded data teams, proactive analytics, metric selection, edge case focus, diverse hiring, early DoorDash stories, global data management, AI in data work.
“For me, analytics is a business impact driving function and not purely a service function.”
“Retention is a terrible thing to goal on. It's almost impossible to drive in a meaningful way in a short term.”
“Sleep can solve lots of problems.”
