Underperforming VC firms persist because the 7-10+ year feedback loop for returns allows them to raise multiple funds before performance is clear. Additionally, most LPs struggle to distinguish between a manager's true investment skill and market-driven luck.
The 'classic' VC model hunts for unproven talent in niche areas. The now-dominant 'super compounder' model argues the biggest market inefficiency is underestimating the best companies. This justifies investing in obvious winners at any price, believing that outlier returns will cover the high entry cost.
There's a surprising disconnect between the perceived brilliance of individual investors at large, well-known private equity firms and their actual net-to-LP returns, which are often no better than the market median. This violates the assumption that top talent automatically generates outlier results.
During due diligence, it's crucial to look beyond returns. Top allocators analyze a manager's decision-making process, not just the outcome. They penalize managers who were “right for the wrong reasons” (luck) and give credit to those who were “wrong for the right reasons” (good process, bad luck).
Many sub-$500M venture funds are over-invested and under-reserved. While venture capitalists like Josh Wolfe predict a 50% failure rate for these "minnows," the Limited Partners (LPs) who fund them are even more bearish, believing the involuntary extinction rate will be closer to 90%.
In a world of highly skilled money managers, absolute skill becomes table stakes and luck plays a larger role in outcomes. According to Michael Mauboussin's "paradox of skill," an allocator's job is to identify managers whose *relative* skill—a specific, durable edge—still dominates results.
Many LPs focus solely on backing the 'best people.' However, a manager's chosen strategy and market (the 'neighborhood') is a more critical determinant of success. A brilliant manager playing a difficult game may underperform a good manager in a structurally advantaged area.
The primary risk to a VC fund's performance isn't its absolute size but rather a dramatic increase (e.g., doubling) from one fund to the next. This forces firms to change their strategy and write larger checks than their conviction muscle is built for.
A common mistake in venture capital is investing too early based on founder pedigree or gut feel, which is akin to 'shooting in the dark'. A more disciplined private equity approach waits for companies to establish repeatable, business-driven key performance metrics before committing capital, reducing portfolio variance.
The majority of venture capital funds fail to return capital, with a 60% loss-making base rate. This highlights that VC is a power-law-driven asset class. The key to success is not picking consistently good funds, but ensuring access to the tiny fraction of funds that generate extraordinary, outlier returns.
AI startups' explosive growth ($1M to $100M ARR in 2 years) will make venture's power law even more extreme. LPs may need a new evaluation model, underwriting VCs across "bundles of three funds" where they expect two modest performers (e.g., 1.5x) and one massive outlier (10x) to drive overall returns.