A startup usually has two important characteristics:
- Innovation: A startup is testing assumptions that haven’t been tried before – sufficiently new technologies, products & services, or markets.
- Growth: A startup has the potential to grow exponentially rather than linearly. It is scalable. This usually happens because technology provides leverage (usually, a marginal cost of production close to 0).
So, a startup is in essence, a business experiment with potential. This means that real startups are prone to failure by definition.
They are testing assumptions, and it’s very likely these assumptions are wrong. The more innovative the startup, the riskier the assumptions and the more likely it is to fail.
When you put this new kind of risk on top of the traditional risks of starting a business (finance/cash flow risks, operational risks, team risks, marketing risks, etc.), it’s no surprise most startups fail.
Example: New Startup vs Non-startup Projects
Imagine you have a new IT consultancy that builds software for your clients. Even though you are a new business and you work with technology, you are not a startup because:
- You are not innovative by definition. You’re providing the same service other IT consultancies all over the world are providing.
- You can grow linearly – you are getting paid per hour, so growth would require hiring new developers, and increasing your costs at a similar rate to your revenue.
One day, you notice that all your clients have a similar problem, so you decide to invest some time in developing your own software to solve that particular problem.
This is a startup project because:
- It’s innovative – it is solving a problem in a new way (your software solution).
- It’s scalable – gaining new users of the software doesn’t increase the costs of running the software linearly.
The likelihood of your consultancy business failing is lower than that of your new software product because the software project is still trying to find product-market fit. Once validated, however, the software project could have more significant returns because of its potential for exponential growth through leveraging technology instead of human capital.
How Many Startups Fail?
So, when you talk about startup failure rates, it’s essential to understand one thing:
- Are you talking about the failure rates of new businesses in general (traditional businesses like the new hairdresser salon included)?
- Or are you only talking about the failure rates of innovative and scalable business ideas?
Failure Rates of All New Businesses
Statistical sources from government institutions are largely concerned with the failure rate of new businesses. This is useful if your project is closer to a traditional business.
In this case, your baseline failure rate would be lower than 90%. One of the most quoted statistics, in this case, is the Business Employment Dynamics report coming from the Bureau of Labor:
- 20% failure rate until the end of the 1st year
- 30% failure rate until the end of the 2nd year
- 50% failure rate until the end of the 5th year
- 70% failure rate until the end of the 10th year
Most newly registered businesses aren’t true startups, so you shouldn’t assume your likelihood to fail in the 1st year is only 20% if you’re trying to do something innovative.
N.B. Some articles out there are quoting those statistics in the context of startups, which is misleading, so be careful!
What about the failure rate for companies that went over Shark Tank? Only 6% have shut down.
Failure Rate Implications
For Startup investors
So why can investing in startups be profitable even with the abysmal failure rate?
It’s because successful startups make up for the unsuccessful ones.
If a startup fund has a portfolio of 100 companies, most of its returns would come from one investment (ideally, a unicorn), followed by the nine successful-but-not-huge companies. The 10 successful startups more than compensate for the 90 failures.
The implication is that startup investors are searching for the home run and are willing to lose money on most of their investments to find that company.
As a founder, you’re unlikely to get funding from startup angels and VCs if you don’t show a lot of ambition and scalability.
This doesn’t necessarily mean that your idea isn’t worth pursuing if it doesn’t fit the investment criteria of VCs. Being a successful founder of a lifestyle business is way better than being an unsuccessful founder of a traditional go-huge or go-home startup.
For Entrepreneurs
If you’re doing anything remotely innovative, you need to accept that you are likely to be wrong. The world is very complex, and most ideas (and the assumptions they carry) turn out to be bad.
A great example is when Twitter acquired Vine to disrupt the video-sharing and social network ecosystem and ended up shutting the app down only a few years later.
That said, simply accepting that you have a 90% chance to fail doesn’t seem like a healthy mentality. There are plenty of ways you can maximize your chances of success. The fact that the average is 90% doesn’t mean you can’t nudge this number in your favor.
Some of the concepts that would help you the most:
For Idea-Stage Startups
You are searching for a product-market fit. The principles of the Lean Startup are extremely important at this stage. The goal is to validate your assumptions as quickly and cheaply as possible and to give yourself time to pivot if necessary.
Get a good grasp of the meaning of MVP, validation experiments, and validated learning. Get used to the agile project management principles when you are in the process of building. Learn to prioritize and change your priorities based on customer feedback.
Here are some findings from the Startup Genome Project:
- Startups need 2-3 longer to validate their market than most founders expect. (The implication here is that cashflow/availability problems can kill the project before you are able to properly test the waters.)
- Founders overestimate the value of the intellectual property before product-market fit by 255%.
- Startups that pivot 1-2 times have 3.6x better user growth and raise 2.5x more money. Startups that pivot 0 times or more than 2 times do considerably worse. (The implication is that it is prudent to secure sufficient time and resources to attempt up to two pivots.)
For Later-Stage Startups
One of the biggest traps is premature scaling. It means over-investment of resources (in the broadest sense) too early in the startup journey.
The Startup Genome Project breaks the startup stages into four: Discovery, Validation, Efficiency, and Scale. It calls startups that scale prematurely inconsistent.Here are some examples of their findings:
- Inconsistent startups write 3.4x more code in their Discovery phase and 2.25x more code in the Efficiency phase.
- Inconsistent startups raise 3 times more capital in the Efficiency stage and 18 times less capital in the Scale phase.
- The self-reported valuation of inconsistent startups before reaching the Scale phase is $10 mil. Consistent startups report $800k.
- Inconsistent startups have 75% more paid users in the Discovery and Validation phases. Consistent startups have 50% more in the Scale stage.
6 Reasons Why Startups Fail
In the in-depth study of our interviews with the founders of 80+ failed startup projects that you can read in full in our Startup Mistakes article, we found that the most common reasons for failure are the following:
1) Marketing Problems (56%)
Marketing mistakes were the biggest killers, and the biggest problem by far is lack of product-market fit.
Don’t invest a lot of time and resources before you are confident people want what you are offering.
Validate your assumptions quickly and cheaply, and if needed – pivot.
2) Team Problems (18%)
Problems like lack of domain knowledge, lack of marketing knowledge (and plan), lack of technical knowledge, and finally – lack of business knowledge are the biggest killers.
Friction within the team, lack of motivation, and lack of availability are also common but less deadly.
3) Finance Problems (16%)
More than 50% of the interviewed founders didn’t have a budget for their project, and 75% were self-funded, yet only 16% pointed to financial problems as the reason for failure.
That’s because you don’t really need a lot of money to test and validate concepts (you need effort). You need money to grow an already validated concept, so financial problems plague mostly exclusively later-stage startups.
4) Tech Problems (6%)
Rarely a big killer, even though the vast majority of the interviewed startups have some kind of technology in their core.
The biggest mistake is over-investment in expensive technology (developer time) before the marketing assumptions have been validated.
5) Operations Problems (2%)
For software startups like most of our interviewees, operational problems are understandably rare. This might not be the case for startups that work with physical products.
6) Legal Problems (2%)
It is largely overestimated and very rarely the reason for failure. That said, heavily-regulated industries like food and finance still present legal obstacles.
Disclaimer: most of the projects we interview are true startups (rather than new traditional businesses) and have some form of technology (usually software) in their core. This means our conclusions might not be that useful for new projects closer to traditional brick-and-mortar businesses. Moreover, we gather the data by interpreting qualitative interviews (rather than surveys), so allow for some error.м