Strategy & Portfolio
Last updated
Quick Answer
A distortion in data or conclusions caused by non-random sampling, common in VC when analyzing success patterns.
Selection bias in VC occurs when analyzing outcomes based only on visible data. Survivorship bias (only studying successful companies) and availability bias (overweighting recent or memorable examples) lead to flawed pattern recognition and investment theses.
In Practice
A VC analyzed 50 successful SaaS companies and concluded 'all great companies have technical co-founders.' But they didn't study the 500 failed companies that also had technical co-founders.
Why It Matters
Selection bias leads to overconfident theses and systematic blind spots. The most dangerous biases are the ones investors don't know they have.
VC Beast Take
Selection bias is why VC conventional wisdom is often wrong. We study the winners and build rules from them, forgetting that the losers often did the same things.
Selection bias in VC occurs when analyzing outcomes based only on visible data. Survivorship bias (only studying successful companies) and availability bias (overweighting recent or memorable examples) lead to flawed pattern recognition and investment theses.
Understanding Selection Bias is critical for founders navigating the fundraising process. It directly impacts deal terms, valuation, and the relationship between founders and investors.
Selection Bias falls under the strategy category in venture capital. This area covers concepts related to the strategic approaches to portfolio construction and management.
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