Unexpected learnings from a few failed startups
Over the last year, I valiantly but ultimately unsuccessfully tried to build a number of different tech startups. Reflecting back on that experience, there are a handful of things I've learned that have genuinely surprised me and I thought I'd share those learnings here on the off chance someone else reads this and finds it helpful in their own entrepreneurship journey.
What I will not do in this article is dissect why the specific startups I pursued were not successful. There are so many blog posts written about "why startups fail" that I don't think I can meaningfully add anything on that topic. Instead I'd like to focus only on my unexpected learnings that I either haven't seen others talk about or are contrarian in nature.
1. Being passionate about startups isn't enough
It is often said that founders need to be deeply passionate in order to build a successful business. The logic being that this passion will carry them through the inevitable hard times that lie ahead to the promised land of startup success.
However, less is said about the nature of the passion required. Personally, I would categorise this passion into either passion for the problem solved or a general passion for just building businesses.
Initially, I believed that simply being passionate about the business of building a business would be sufficient to keep me going. However, when faced with good opportunities to build businesses that had a clear path to commercial viability, I quickly discovered that if I didn't care about the problem I couldn't even get out of bed.
While there are likely a few rare unicorns out there who are able to build startups around problems they don't really care much about, I strongly suspect that the majority of us mere mortals can only build companies around topics where we have prior experience and an existing emotional attachment.
2. Solving a big problem doesn't equal customers
Startup up law #1, find a large unsolved problem, and if you can solve this problem then eventually with enough sales and marketing, people will pay you to solve it.
In most cases the above statement holds true, but not always. Below are a few of the exceptions that we encountered, and I'm sure there are more.
- A highly consolidated market: In a market with a small number of very large customers that compete, customers may not be willing to adopt solutions that are used by rivals for fear they will not be able to differentiate themselves.
- Mission criticality: Some problems are so big they can solely determine the success of the customers business. In these cases, it is seen as too risky to rely on a vendor solution.
- Data sensitivity: In situations where highly sensitive customer data is required, the risk of sharing that data may outweigh the benefit gained from solving a problem.
3. Execution isn't important (at the early stage)
"Ideas are cheap, execution is everything", I've seen and heard this in countless presentations and articles about building businesses, but fundamentally I disagree with it for early-stage businesses.
Yes, there are many examples of entrepreneurs who have built world-beating companies with unoriginal ideas by executing well (e.g. Zoom, Google, Facebook). However, each of these businesses started with the foundation of a solid idea, even if it wasn't original.
At the earliest stages of a business and especially if you are defining a new category, if you do not validate a problem and idea that are viable, it will not matter how well you execute on that vision. Conversely, if you have a great unique idea, you could find early success even with lacklustre execution.
Venture Studio Product Design Partner | Boost Product Adoption by 30% | Product UX/UI Specialist
3 年Agreed with your points, and particularly the last one. Great ideas “sell” themselves
Product at Andela | Delivering a better experience for scaling remote engineering teams globally
3 年thanks for sharing, Andrew! this is awesome (the learning part-- the failed startups part stinks, as i can attest to). hope you're well and look forward to hearing about what you get into next.
Staff Software/ML Engineer
3 年agree with all points! Glad we failed so fast ??