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#244 – Small Funds, Big Wins: The Case for Lean Venture Strategies
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#244 – Small Funds, Big Wins: The Case for Lean Venture Strategies

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Doug Dyer
May 22, 2025
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#244 – Small Funds, Big Wins: The Case for Lean Venture Strategies
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If you’ve been following along—#218, #219, and #223—you already know the thesis: smaller is not a bug in venture capital; it’s a feature.

  • #218 Size Matters: Small vs. Big VC Funds (5x+ vs. 2x+)

  • #219 Size Matters in VC (Cont'd)

  • #223 Small Teams Are The Future & VC Impact

James Heath’s recent piece, Small Funds, Big Wins, adds a data-driven lens to this thesis. It’s not just that smaller funds can work—it’s that, when paired with manager selection discipline, they may outperform by design.


Why Smaller Funds Deliver Outsized Results

Across a dataset of 1,700 venture funds, the distribution is clear:

  • Top quartile fund size: $65M

  • Top decile fund size: $38M

“In an ecosystem that often equates ‘bigger’ with ‘better,’ this is a counterintuitive truth.”

In #218, we covered how smaller funds need fewer outcomes to return capital. Heath refines the point: a $200M exit can reshape a $50M fund—but has near-zero effect on a $500M vehicle. Small funds benefit structurally from ownership concentration and velocity.

“Smaller funds can afford to move earlier, act faster and optimize for ownership in a way large, AUM-driven funds simply can't.”


Selection > Scale

But fund size alone isn’t enough. In #219, we warned against the false comfort of platform-scale logos. Heath echoes this: the top 5% of managers outperform because they stay focused and don’t scale just to grow AUM.

“The best funds are not solely chasing AUM—they’re chasing alpha.”

This is where LP discipline matters. Emerging managers operating sub-$100M strategies aren’t just check-the-box exposure—they may be core DPI drivers in the next cycle.


What Still Works in 2024

While average fund sizes have ballooned to $170M+, the median new VC fund has held steady at $24M since 2015. In #223, we noted how small, focused teams consistently outperform due to faster cycles, deeper ownership, and less internal drag.

“Despite the ballooning average, the flat median tells a story: alpha doesn’t scale linearly with size.”

The structural logic of small funds still holds—but the entry dynamics are changing:

  • Seed rounds are priced at $30–50M post

  • Entry checks now exceed $10M

  • Early-stage risk is being priced like Series A—without the governance rights or milestones that once came with it

“What looks like seed increasingly feels like Series A—minus the protections.”


The Smart Play for LPs? Back the 20, Not the 2

Heath’s guidance is a perfect capstone to the thread we’ve been pulling:

  • Don’t chase mega-funds just because they raise big.

  • Focus on the 20% of GPs building intentionally small, high-conviction portfolios.

  • These GPs are optimized for ownership, portfolio construction, and founder alignment—and that’s where real returns come from.

“Keep backing the GPs running for the 20 instead of walking for the 2.”


TL;DR – Small Funds Are Still the Big Opportunity

  • Smaller funds outperform. Top decile = $38M; top quartile = $65M

  • Math is on their side. $200M exits matter more in a $50M fund

  • Selection > scale. The best managers avoid unnecessary AUM growth

  • Strategy still works. Median new fund size is flat since 2015

  • Risks are rising. Seed is now priced like Series A without safeguards

  • Back the 20. LPs should prioritize emerging managers, not mega-funds


In short: this isn’t a contrarian take. It’s a data-supported shift in the LP mindset. Smaller funds—run by focused, under-the-radar GPs—remain the highest-leverage bet in venture today. And if you’ve been reading since #218, you already knew that.


Tools to Navigate Small Fund Strategy

If you’re an LP evaluating smaller GPs, or a fund manager sharpening your pitch, our premium toolkit was built for you.

Each resource helps you model fund outcomes, understand distribution dynamics, and benchmark DPI vs. carry under different structural assumptions.

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