Building a world-class data org | Jessica Lachs (VP of Analytics and Data Science at DoorDash)

1. Adopt Centralized Data Org

Structure your analytics team as a central model, rather than embedding them in business units, to ensure a consistent high talent bar, clear growth opportunities, standardized methodologies, and a strong team culture.

2. Drive Business Impact with Analytics

Position analytics as a business impact driving function, not merely a service. This means finding opportunities, having a point of view on decisions, and answering ‘so what do we do now’ instead of just ‘why’.

3. Use Short-Term Proxy Metrics

Identify and measure short-term proxy metrics that reliably drive desired long-term outcomes. Long-term metrics like retention are often too slow to meaningfully impact in the short term, hindering quick experimentation and iteration.

4. Keep Metrics Simple and Understandable

Choose simple, intuitive metrics that are easily understood and discussed across the company, even if not perfectly comprehensive. These are more effective at driving real outcomes than complex, composite scores that nobody understands.

5. Quantify Levers in Common Currency

Quantify all business levers (e.g., price, delivery times) in terms of a common currency like Gross Order Value (GOV) or volume. This allows for quick, informed tradeoff decisions across different teams and initiatives.

6. Target Edge Cases and Fail States

Actively seek out and set concrete goals around eliminating rare but costly edge cases and fail states (e.g., ’never delivered’ orders). These disproportionately lead to churn and expense, and are often missed by focusing only on average metrics.

7. Cultivate Extreme Ownership

Instill a culture of extreme ownership over outcomes, encouraging team members to go beyond their defined roles (e.g., data scientists calling customers) to solve problems and achieve goals, doing whatever is needed to win.

8. Intentionally Carve Out Exploratory Time

Be intentional about carving out time for exploratory work and deep dives, setting goals for self-directed insights (e.g., hackathons). This prevents valuable long-term opportunity-finding from being overshadowed by immediate inbound requests.

9. Communicate Tradeoffs for Prioritization

When faced with multiple tasks, communicate the tradeoffs to business partners. Ask if new requests are more important than existing priorities, making them aware that adding new work means something else must drop.

10. Hire for Curiosity and Self-Motivation

Prioritize hiring for curiosity and self-motivation, as these traits drive individuals to proactively investigate anomalies and opportunities without being explicitly told, adding significant value to the team.

11. Assess Reaction to Being Wrong

During hiring, observe how candidates react to being told they are wrong or presented with new information. Their ability to pivot, take new context, and make decisions with incomplete data is a crucial soft skill.

12. Develop a Point of View

Cultivate the ability to form a point of view and make decisions even when presented with incomplete information. This reflects real-world scenarios where perfect data is rarely available, and a direction must be chosen.

13. Identify Missing Data Gaps

Proactively consider what data might be missing or unobservable (e.g., login failures where users don’t enter the system). These gaps can hide critical problems and opportunities for improvement that won’t appear in standard metrics.

14. Solve Problems from First Principles

Approach problem-solving by focusing on immediate needs and unblocking yourself using first principles. This helps avoid getting overwhelmed by the larger, long-term vision and enables organic learning and growth.

15. Hire for Diverse Backgrounds

Actively seek to hire individuals from diverse professional and educational backgrounds into your data team. This creates a unique environment where varied expertise and perspectives can foster mutual learning and growth.

16. Continuously Re-evaluate Prioritization

Maintain good hygiene by having ongoing conversations with business partners to constantly re-evaluate and align on team priorities, ensuring work remains focused on the most impactful tasks.

17. Build Goodwill with Quick Asks

Occasionally fulfill quick, easy requests from partners, even if not top priority, to build goodwill and strengthen relationships, especially when it takes minimal effort.

18. Empower Non-Technical Users with AI

Leverage AI tools (e.g., chatbots for SQL query editing) to empower non-technical users to self-serve data needs. This reduces the analytics team’s bandwidth burden and increases overall company productivity.

19. Embrace a Customer-First Culture

Cultivate a ‘customer-first’ culture that extends to all stakeholders—consumers, dashers, and merchants—to ensure empathy and focus on their experiences, which is critical for business success.

20. Implement WeDash Program

Institute a program like ‘WeDash,’ where all employees regularly engage in customer-facing roles (e.g., dashing, customer support) to build empathy with all user groups and identify product bugs.

21. Learn from Bad Metrics

Recognize that significant learning about effective metric selection often comes from the experience of choosing and working with ineffective or ‘bad’ metrics.

22. Practice Truth Seeking

Actively practice truth-seeking by diligently discerning fact from fiction amidst widespread misinformation, recognizing this as a critical individual responsibility and company value.

23. Sleep on Difficult Problems

When facing a difficult problem or crafting a response to a tense issue, allow yourself to sleep on it, as a fresh perspective in the morning often leads to better solutions and clearer communication.

24. Use Libby App for Reading

Utilize the Libby app to access and enjoy books from your local public library, supporting community resources and personal reading habits.

25. Try Korean Sunscreens

Experiment with Korean sunscreens, such as those from Beauty of Joseon or Isntree, as they are noted for their superior quality and pleasant wear compared to U.S. alternatives.