I was a guest on a podcast talking about early-stage startups recently and the host asked: “We know most startups fail, but the number one reason is they don’t meet a market need. Why is that?“
It’s true, the vast majority of startups fail. Depending on which study you’re looking at, the number is anywhere between 75 and 90%.
My answer on the podcast had more to do with the tendency for entrepreneurs’ vision and personal conviction to override what the market is telling them.
Don’t get me wrong, I’m a believer that in a startup’s early-stage, the entrepreneur’s vision is a legitimate compass for setting product strategy despite what conventional wisdom or market research might suggest.
The trade-off, of course, is that most of the time that vision will not find its way to a sustainable business, but when it does the opportunity is exponentially greater.
And even with market research and a well-defined target customer and maybe even some revenue on day one, the business can still fail. Growing a startup out of the early-stage is very difficult to do for a billion reasons.
The rest of the interview was mostly spent chatting about customer research, how much data is enough to course correct your product strategy, identifying market opportunities, etc. All things that are intended to give your startup a better chance of avoiding that big ol’ number that represents failure.
It was a fun conversation and you can listen to the episode here.
But, I was more interested in thinking through how people like you and me should deal with that inherent uncertainty: That sometimes no matter what you do, your early-stage startup will probably fail.
If you’re working for or running a startup, or if you hear the siren song of entrepreneurship and are thinking about leaving a salaried position, a 75-90% failure rate is a frightening statistic!
I’m writing these very words as a business owner running a consulting practice while I bootstrap my SaaS, Feature Audit, in whatever spare time I can manage. Objectively, the odds are that both of these ventures will fail. So, how do I sleep at night?
Depending on the week, not very well! 😂
With startups, the highs are high, and the lows are low. Heidi Klum is talking about fashion when she says it, but it applies to entrepreneurship as well: “One day you’re in. And the next day, you’re out.”
Seriously though, the stakes are high. I’ve got a wife and three kids, so failure wouldn’t be a self-contained event. Your specifics are probably different, but the stakes for taking a risk and betting on yourself are most likely similar.
There’s just no way around it, if you want to start a startup or roll the dice and join an early stage, unproven business, you have to decide where on the spectrum you are comfortable living:
Certainty/Comfort/Establishment => Uncertainty/Risk/Freedom
If you’re too risk-averse, you’ll never jump in. The water is just too deep.
And on the other hand, if you’re overly risky and dive in blindly without any sort of plan, you’re even more likely to fail and find yourself as a picture perfect example of the 75-90%.
Find Your Place on the Spectrum of Certainty
Fortunately, the spectrum of certainty does exist and there are more choices to be made other than: a) Bootstrapped Startup, or b) Multi-national Enterprise.
If you want to join a startup, there’s a big difference between a seed-stage company and one that’s in their fifth year of profitability. The trade-off is in how much equity you’ll get to participate in.
If you want to start a startup, there’s a big difference between starting at $0 in the bank and sucking it up for a while to put 9-months of expenses in the bank first. The trade-off is in how long you’ll need to be patient.
As in most things, the “right” answer is contextual and personal, and you can’t answer it without knowing yourself and what your season of life might call for. What’s more, the “right” answer isn’t even right, it’s more like “relatively close to optimal.” 🤓
But hey, if you’re dipping your toe in startups and entrepreneurship, you’re probably already comfortable with that kind of ambiguity!