👋 Welcome to the 21 new readers who have joined this week and thank you for the feedback received. Please keep it coming!
In this edition, we will go into:
My “boring” framework for evaluating managers.
A few of my favorite reads this week (including one on airline miles every LP will relate to)
We’ll round off with fundraise announcements over the last week
So let’s get to it.
/ Self-promotion
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My “boring” framework for evaluating managers
First off: I don’t think there’s anything groundbreaking about the framework I used to evaluate GPs. Most LPs will recognize the broad categories.
What counts is how you apply it - the discipline, consistency, and detail you put into each analysis.
For me, that meant putting every GP through the same lens, and scoring not only each area but also each sub-category on a simple 1–5 scale. It wasn’t scientific, but it made us continuously hone our judgement - and it revealed “how we really felt” about a manager, not just what the numbers or narratives suggested.
The development: This became especially valuable as traditional metrics grew easier to manipulate, making gut-check evaluation more important than ever.
The “perfect GP” (in theory)
A proven strategy with a history of top-quartile returns
A team that’s stable and motivated for the next decade
Terms that keep incentives aligned
👉 In practice? I’ve never found one that ticks every single box.
Two examples to ponder
Axcel (Denmark):
Their 2007 vintage fund is the stuff of legends. Pandora’s 40x return helped deliver ~5.5x net for LPs.
The brand name opened doors and guaranteed invites to every relevant process.
But: no one believes Pandora is repeatable. Strip it back and performance was heavily skewed toward one investment. Add partner retirements, and the story became as much about succession as returns.
Audax (U.S.):
Famous for its buy-and-build strategy. Fund VII raised $5.2bn and plans 33–36 investments - far above a typical mid-market fund.
The model spreads risk and creates a more even distribution of returns - too many deals for performance to hinge on a single outlier.
But: can the model scale consistently as fund sizes grow?
The tradeoffs
These are the kinds of tradeoffs that show up again and again.
That’s why I leaned on a simple framework as an LP. It guided everything - from the first pitch meeting to onsite diligence and ongoing monitoring.
The framework at a high level
📊 Performance: The enabler to go into any diligence for me. It is both a matter of absolute and relative returns, as well as the distribution of returns and a lack of dependency on outliers.