Growth Team as a Rigor Forcing Function
Hire a growth leader early — the second-order effect is that it exposes everything you haven't measured.
- Difficulty
- Moderate
- Time to result
- ~months to results
- Steps
- 4
- Confidence
- 92%
Deng's first move at Instagram, Uber, Airtable and ChatGPT was to build a growth team — not primarily to drive growth, but because a growth leader's instinct to demand data uncovers how little you've logged and how non-rigorous your product understanding is. Because growth PMs are tied to outcomes, the org actually listens to them, changing the team's DNA toward measurement.
Origin
Peter Deng's repeated playbook across Instagram, Uber, Airtable and OpenAI/ChatGPT.
Core principles
- 01You wouldn't fly a plane without instruments, so don't run a product without instrumentation
- 02A growth leader's questions surface unlogged data and untested hypotheses as a side effect
- 03Growth beats a standalone analytics/data-science team because growth is tied to outcomes, so people listen
- 04This 1-to-10 rigor is what sets up successful scaling from 10 to 100
How to run it
- 1
Build a growth team early
In the 1-to-10 phase, make hiring a growth leader one of your first moves, treating it as a simple razor that will unlock the right behaviors.
- 2
Let their questions expose the gaps
A strong growth PM asks 'why is this happening?' and 'get me the data on X, Y, Z' — revealing what you never logged. Log those things.
Pro tip Hire the archetype who is genuinely wired to experiment; the questions come for free.
- 3
Iterate into rigorous analysis
With new data logged, keep asking what correlates with what and forming hypotheses, turning a product that 'seems to work' into a rigorous system.
- 4
Choose growth over a pure analytics team
Prefer a growth leader tied to outcomes over an analytics/data-science team whose insights may go ignored.
Pro tip Have the growth leader partner with data science so the whole business gets more rigorous.
Watch out An analytics team with no outcome ownership risks producing insights nobody acts on.
In the wild
Deng recalls walking into Instagram and asking Kevin Systrom how many users they had — 'Well, we don't really know... there are a lot and we don't really know.' Building a growth team surfaced what wasn't logged.
→ Instagram usage quadrupled in two years during the period Deng ran product and built growth rigor.
Common mistakes
Standing up an analytics team instead of a growth team
Analytics or data-science teams generate insights but aren't tied to outcomes, so 'no one really cares' and nothing changes; a growth leader owns growth and therefore drives the questions and the follow-through.
Scaling a product you can't instrument
Running a product without knowing your numbers is like flying a plane without instruments — you can't see what's working, so growth and scaling decisions are guesswork.
Is it for you?
Best for
Founders and product leaders at the 1-to-10 stage who sense the product works but lack measurement rigor
Not ideal for
Pre-product-market-fit teams still searching for the core value, where instrumentation is premature
From the transcript
“one of the first things I did was always to build a growth team”
“you're going to uncover how much stuff you have not yet”
“if you build an analytics team or a data science team it's possible that no one's going to listen to them”
“just like how you wouldn't fly a plane without instruments”
From the episode
From ChatGPT to Instagram to Uber: The quiet architect behind the world’s most popular products
Peter Deng