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📢 Why Your Startup Idea Isn’t Big Enough for Some VCs?
Investors often tell founders that their startup doesn't align with their investment thesis or some generic response like “not this time (not investing this time)” leaving most founders confused.
This week, I had a call with a founder who asked me the same question: What do investors mean by 'you are not the perfect fit, this time?’ There are several reasons for this, such as the startup not aligning with the investor's thesis in terms of industry, funding amount, or other factors.
One common reason for rejection is when investors believe that the startup is not big enough for venture capital (VC) investment. But what does this mean?
During pitch sessions, investors focus on one key question: "Can this startup become worth a billion dollars?" If they don't see that potential, the startup is often rejected.
Let's understand - why VCs are inclined to invest in big ideas.
Source: Google Images
VC functions with a power law, the majority of a fund’s returns come from a small percentage of investments.
Because of this, Venture Capital need to know if a single investment can return the entire fund. What does it mean? Let’s understand this 👇
Fig: Power Law In Venture Capital
As Bill Gurley said “Venture capital is not even a home-run business. It’s a grand slam business.” This is where the Return The Fund (RTF) analysis comes into play.
Look at the below Data from 2004-2013.
https://www.sethlevine.com/archives/2014/08/venture-outcomes-are-even-more-skewed-than-you-think.html
If we assume an exit distribution, over 60% of a fund’s investments are 0–2x their money, With the remainder falling between 2–5x, a “unicorn” type 10x+ outcome can put a venture fund into the desired 3x fund returns that put them among the top performers in VC.
Your 1–3 investments that “return the fund” and probably even more (the grand slam), are what will make or break you, While the other 2x-5x investments create additional alpha.
Let's understand the math behind the Return The Fund (RTF) to get a better idea.
The math for an RTF analysis is pretty simple:
Fund Size / % owned at exit = Minimum Viable Exit
To get a clear idea - let's take an example of an autonomous vehicle startup built on the blockchain, X raising a $2M seed at a $10M Post money valuation (Selling a 20% stake).
VC Fund A is a $50M seed fund investing $1M.
$1M/$10M valuation = 10% ownership
In order to return the fund, X must exit for (50/.1) = $500M
But over the period, Fund A wasn't able to invest in the next rounds (not maintain pro-rate thing ) so their stake got diluted. Assume dilution by 20%.
With this dilution by 20% - the real return of the fund number is $625M ($50M/.08). So in order to pass RTF (Return To Fund) analysis, VC Fund A must believe that X will exit for at least $500M and more realistically $625M. This is for some small funds like seed.
Now let’s look at a larger fund model.
VC Fund B is a $250M fund investing $1M in X.
$1M/$10M valuation = 10% ownership
Return to Fund calculation: VC Fund B has to believe that X will exit for $2.5B ($250M fund / 10% stake).
Assume this fund is able to invest in further rounds and able to get 5% extra which makes the stake 15% at exit.
VC Fund B has to believe that X will exit for $1.66B ($250M/15%) in that increased ownership scenario.
But does the company really exit at $1.66B or more? What’s the past data say? -
Let's look into this. If you look at data on equity ownership at exits, the image below:
Data till 2016 - on VC Backed Startups Exit
As an investor, the difference between a company exiting for $500M vs. $2.5B is not trivial. Less than 10% of all VC-backed exits in 2016 were $500M+, per CB Insights.
As a founder, this trickles down to thinking about their potential investor’s philosophy. While some startups are built to exit in the 100 of millions of dollars, Larger funds could push through their natural exit points in order to go for broke and hit a grand slam which is unlikely to occur. Return to the fund (RTF) is a good barometer, but just one data point in the Due Diligence Process.
It is a quick way to gut-check ownership and investment size and also allows investors to think about how they will need to build their positions over time. But while this thought process is generally useful, like all things in startups, there are outliers.
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Featured Article:
“How to Find the Right Problem To Solve?” - YC Strategy
One of the most common reasons for startup failures is founders attempting to solve the wrong problem. About 99% of founders choose the wrong problem to solve which leads to the failure of a startup from the first day itself.
Successful founders, on the other hand, choose the right problem to solve. Each founder has their own experience in identifying the problem, but most of them are not aware of how to determine if it is the right problem to solve.
Source: Google Images
So, Y-Combinator shared a practical approach to finding - whether a founder solving the right problem or not. YC Shared that…..
Find the Problem which is —
Popular
Growing
Urgent
Expensive
Mandatory
Frequent
Let’s decode each one of these:
Popular: Find A Problem that a lot of people are facing. You should avoid problems with only a small number of people are facing.
Growing: Find the problem which is growing, so a large number of people will face problems in the coming time.
Urgent: The problem needs to be solved very very quickly.
Expensive To Solve: If you’re able to solve it then you can charge a lot of money for potential.
Mandatory: Problems that are mandatory right so people can see the problem and use your product/service.
Frequent: over and over again (— people are gonna encounter the problem over and over again and often in a frequent time interval.
A successful startup has one of the aspects in their problem and even some have multiple aspects, But the most important thing they have is Frequency as it gives opportunities to convert some of the parts (which is generally the large part of it).
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