The Twenty Minute VC

Chandra Narayanan: Top 5 Lessons from Leading Analytics at Facebook | E1126

Chandra Narayanan is one of the growth and analytics OGs having spent 7 years at Facebook leading analytics for the Facebook App and for Instagram. After Facebook, Chandra became Chief Data Scientist @ Sequoia Capital, helping Sequoia, find, select and help the best entrepreneurs in the world. Today, Chandra is the Founder and CO-CEO @ Sundial, building products to help builders make meaningful use of data to fulfil *their* mission. ----------------------------------------------- Timestamps: (00:00) Intro (00:44) Seminal Advice from Rohan at PayPal (02:35) Importance of Fixing What’s Broken (04:09) Toughest Situation at Facebook (05:26) Lessons Learned from Facebook (05:54) Importance of Focusing on Impact (07:29) Difference in Motion & Progress (08:37) Data-Driven Decision Making (17:36) Building World-Class Teams (21:10) Defining Growth & Importance of Hypotheses (21:50) Selecting & Changing North Star Metrics (32:47) First Growth Hire (36:28) Centralized vs. Decentralized Growth Teams (39:30) Hiring for the Future Company (42:34) Challenges of Influencing (47:04) Mistakes in Influencing (48:27) Hiring Exceptional People (51:54) Skills for Growth & Analytics Teams (55:05) Importance of Indexing (58:55) Identifying Performance Issues (01:02:05) Hiring Mistakes (01:09:08) Timing of Performance Improvement Plans (01:11:48) Why Senior Executives Fail (01:16:00) Quick-Fire Round ----------------------------------------------- In Today’s Episode with Chandra Narayanan We Discuss: 1. From Working on the Weather to Leading Analytics at Facebook: How did Chandra make his way from analyzing weather patterns to leading analytics for Facebook? What does Chandra know now that he wishes he had known when he started his career in growth? How did one piece of advice from his manager at Paypal change Chandra’s mind forever on “quitting” and when to “quit”? 2. Growth and Analytics 101: What does growth mean to Chandra? What is it? What is it not? When is the right time to hire a growth team/person? What is the right profile for the first growth hires? 3. How to Hire the Best Growth Teams in the World: What are the must-ask questions when hiring for growth? How does Chandra use case studies to determine the quality of a candidate? What does Chandra believe are the four main reasons people go to work? What are the three different types of execs in tech? How do you know when you need each one? 4. Lessons from Leading Analytics at Facebook and Sequoia: What are 1-2 of Chandra’s biggest takeaways from leading analytics at Facebook? What does Chandra believe are the two core skills needed to do analytics well? How can you easily test if someone is good at analytics? How did being Chief Data Scientist @ Sequoia change Chandra’s perspective on growth? ----------------------------------------------- Subscribe on Spotify: https://open.spotify.com/show/3j2KMcZTtgTNBKwtZBMHvl?si=85bc9196860e4466 Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-twenty-minute-vc-20vc-venture-capital-startup/id958230465 Follow Harry Stebbings on Twitter: https://twitter.com/HarryStebbings Follow Chandra Narayanan on Twitter: https://twitter.com/cncoold Follow 20VC on Instagram: https://www.instagram.com/20vchq Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/contact ----------------------------------------------- #20vc #harrystebbings #venturecapital #founder #ChandraNarayanan #sundial #meta #paypal #facebook #instagramyoutube #hiring

Chandra NarayananguestHarry Stebbingshost

Mar 12, 20241h 22mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

From Facebook Analytics to Sequoia: Building High-Impact Growth Machines

Chandra Narayanan reflects on lessons from leading analytics and growth at Facebook and later driving data efforts at Sequoia, emphasizing character, impact, and rigorous thinking over raw activity. He contrasts motion vs. progress, outlines practical frameworks for defining and measuring impact, and explains why North Star metrics and counter-metrics matter. A major theme is how to build and scale world-class growth and analytics teams: hiring for slope vs. asymptote, centralizing growth early, and focusing on impact per capita. He also dives into influence as an art, executive failure modes, and why growth is far harder in practice than most founders realize.

IDEAS WORTH REMEMBERING

5 ideas

Prioritize character-building over quick exits from hard situations.

Staying at PayPal to ‘fix things before quitting’ taught Chandra resilience; that muscle later helped him withstand political pressure and near-firing at Facebook when he insisted on telling uncomfortable truths with data.

Optimize for impact, not activity—avoid confusing motion with progress.

Chandra defines impact as moving a key metric, influencing product decisions, or improving processes; if work doesn’t fit one of these, you’re likely just ‘busy’ without creating real value.

Use a clear impact framework and North Star metric, but keep it movable.

At Facebook, impact was structured around moving a North Star (e.g., MAU/DAU) via input levers like friends added or advertiser count; a good North Star is tied to mission, has real levers, and is periodically revisited as the product or market changes.

Centralize growth early; decentralize only after patterns and culture are strong.

In early stages, a small, centralized growth team concentrates scarce talent, codifies best practices, and transfers learnings across surfaces; as surface area expands, embedding growth into product teams makes more sense.

In analytics, excel at indexing and ‘so what’ questions to create action.

Most analysis reduces to benchmarking (over/under-indexing vs. an appropriate baseline) and then asking whether the observed difference is material to the main goal; this separates smart insight from truly actionable insight.

WORDS WORTH SAVING

5 quotes

You never want to be a quitter. Set things right, fix things.

— Chandra Narayanan

Impact is making sure you don’t confuse motion with progress.

— Chandra Narayanan

If you’re not doing one of these—moving a metric, influencing a product decision, or changing a process—you’re probably not having impact.

— Chandra Narayanan

Every large data problem can be reduced to a small data problem.

— Chandra Narayanan

The more senior you are, the main skill I look for is: can you simplify?

— Chandra Narayanan

Character-building, resilience, and not quitting prematurelyImpact vs. activity: motion, progress, and impact frameworksDefining growth, North Star metrics, and counter-metricsVenture data at Sequoia: sourcing, due diligence, and saying ‘no’ fastBuilding and structuring high-impact growth and analytics teamsInfluence, stakeholder management, and decision-making with dataHiring philosophy: skills, slope vs. asymptote, and executive failure

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