The Failure Rate of Startups: How Many Startups Fail and Why?
- 9 out of 10 businesses fail.
- 7.5 out of every ten venture-backed businesses fail.
- In the first year of operation, two out of ten new enterprises fail.
These are some of the most commonly made claims about startup failure. While those statistics may be helpful, they may also be deceptive if used in the incorrect context.
What Is a Startup and Why Does It Fail?
In the broadest sense, it is a new company in its early phases of development.
On the other hand, this definition is far too broad and, as a result, misleading. A new hairdressing salon is likewise a new business in its early growth phases, but most individuals in the startup industry would say it isn’t a startup.
A typical startup has two key characteristics:
A startup is putting to the test assumptions that have never been put to the test before, such as sufficiently novel technology, goods & services, or markets.
Growth: Rather than growing linearly, a company has the potential to develop exponentially. It’s adaptable, and this frequently occurs due to technology’s ability to create leverage (usually, a marginal cost of production close to 0).
As a result, a startup is essentially a possible business experiment. As a result, genuine startups are doomed to fail by definition. They’re putting assumptions to the test, and these assumptions are probably incorrect. The riskier the assumptions that the startup is testing, the more likely it is to fail.
It’s no wonder that most startups fail when you add this new type of risk to the usual dangers of launching a business (finance/cash flow risks, operational risks, team risks, marketing risks, and so on).
New Startup vs Non-Startup Projects, as an example
Assume you’ve launched a new IT consulting business that specializes in software development for your clients. Even if you are a new firm that deals with technology, you are not a startup since you are not inventive. You’re providing the same service as other IT consulting companies worldwide.
You can grow linearly since you are paid per hour; therefore, increasing your firm would need to employ more developers, increasing your expenditures at a similar rate to your revenues.
You notice that all of your clients have the same problem one day, so you decide to spend some time designing your software solution to solve it.
This is a startup initiative because It’s inventive — it’s a novel solution to a problem (your software solution).
It’s scalable, so adding additional users doesn’t raise the cost of running the software linearly.
Because the software project is still striving to achieve product-market fit, the chances of your advisory firm failing are smaller than the chances of your new software product failing. However, once confirmed, the software project’s potential for exponential expansion through technology rather than human capital might result in higher profits.
What Percentage of Startups Fail?
To understand startup failure rates, it’s essential to know what you’re talking about: Do you mean failure rates for new businesses in general (including traditional companies like the new hairdresser salon), or are you talking about the failure rates of new companies in particular?
Or are you just interested in the failure rates of scalable and creative company ideas?
All New Business Failure Rates
Statistical data from government agencies are primarily concerned with the general failure rate of new firms. This is helpful if your project is more conventional. Your baseline failure rate would be less than 90% in this situation. The Bureau of Labor’s Business Employment Dynamics report is one of the most often cited data in this case:
- The failure rate of 20% till the end of the first year and 30% until the end of the second year
- Until the conclusion of the fifth year, there is a 50% failure rate.
- Until the tenth year, there was a 70% failure rate.
- Most newly registered firms aren’t actual startups, so don’t think that if you’re attempting to do something original, your chances of failing in the first year are just 20%.
Rates of Scale-Up Failure
The vast bulk of venture capital data focuses on natural, innovative, and scalable businesses. On the other hand, venture capitalists prefer growth-stage companies, sometimes known as scale-ups. They’re actual businesses, but most of them have avoided one of the most severe risks that entrepreneurs face: the search for product-market fit. They have evidence that consumers want what they have to give (this proof is how they attract venture capital).
As a result, their failure rates would be lower than early-stage companies. Harvard Business School lecturer Shikhar Ghosh reported in the Wall Street Journal that 75 per cent of venture-backed companies never return investors’ cash, and 30-40% of the time, investors lose their entire investment (He uses a database of 2000 venture-backed businesses for his research.)
However, because just 0.05 per cent of startups receive venture capital investment, this figure does not apply to most new enterprises, particularly those in the early stages of development.
All Startup Failure Rates:
Of course, early-stage (concept stage) businesses are at the most significant risk and have the highest failure rates. Because a substantial portion of such initiatives stays under the radar, it’s challenging to claim accuracy regarding failure rate figures. Most early-stage enterprises are sponsored by the founders, their family, and friends rather than by funds or other institutions that keep a dataset.
You don’t need a legal corporation to test an assumption; thus, many early-stage startup initiatives don’t register one. Once you start producing money, you’ll need one.
Business failure rates of 9 out of 10 are often cited. It appears to have originated from the Startup Genome study (some of their more recent reports claim that only one in 12 entrepreneurs succeed).
For most individuals, the statistic’s exact correctness is irrelevant. The reality is that startups are incredibly dangerous, as seen by our expanding collection of failed startup founder interviews and our Startup Cemetery, but also extremely rewarding, as evidenced by our startup success story interviews.
Implications of Failure Rates
- For Startup investors
So, despite the high failure rate, why might investment in startups be profitable?
It’s because successful startups compensate for their failures.
When a startup fund invests in 100 companies, the one most tremendous success (ideally, a unicorn), followed by the nine successful-but-not-huge enterprises, would provide the majority of the returns. The ten successful startups outnumber the 90 failures by a factor of ten.
The inference is that startup investors are looking for the home run and are prepared to lose most of their investment money to find it. This implies that if you don’t show a lot of ambition and scalability as a founder, you’re unlikely to acquire an asset from startup angels and VCs.
If your project doesn’t suit the investment requirements of VCs, that doesn’t imply it’s not worth pursuing. Being a successful lifestyle business entrepreneur is far superior to failing to launch a standard go big or go home startup.
- For Entrepreneurs
You must embrace that you will almost certainly be incorrect if you do anything unique. Because reality is so complicated, most ideas (and the assumptions they include) are terrible. The acquisition of Vine by Twitter to disrupt the video-sharing and social network ecosystem resulted in the app being shut down only a few years later.
However, recognizing that you have a 90% probability of failing does not appear to be a healthy mindset. There are several techniques to improve your chances of success, and the fact that the average is 90% doesn’t imply you can’t make a positive difference.
- For Idea-Stage Startups
You’re on the lookout for a product-market fit. At this point, the concepts of the Lean Startup are critical. The idea is to confirm your assumptions as rapidly and inexpensively as possible, giving oneself enough time to pivot if required. Learn the definitions of MVP, validation experiments, and validated learning.
When you’re constructing anything, become acclimated to agile project management techniques. Learn to prioritize and adjust your priorities depending on input from customers.
The Startup Genome Project’s conclusions are as follows:
Most entrepreneurs underestimate how long it takes for a startup to prove its market. (The implication is that cashflow/availability issues can destroy a project before you’ve had a chance to test the waters thoroughly.)
Before product-market fit, founders overestimate the value of intellectual property by 255 per cent.
Startups that pivot 1-2 times expand their user base 3.6 times faster and raise 2.5 times more money. Startups that pivot 0 or 2 times perform much worse. (The suggestion is to set aside enough time and resources to try up to two pivots.)
- For Later-Stage Startups
Scaling too early in a project is a common mistake, and it entails excessive resource expenditure (generally) too early in the starting process. The Business Genome Project divides the four stages into four categories: discovery, validation, efficiency, and scale. Startups that scale too quickly are labelled as inconsistent. Here are a few examples:
Startups that are inconsistent write 3.4 times more code in the Discovery phase and 2.25 times more regulation in the Efficiency phase.
Startups raising varying amounts of money raise three times more during the Efficiency stage and eighteen times less during the Scale stage.
Inconsistent startups have a self-reported valuation of $10 million before they reach the Scale phase—startups with a track record of success report an average of $800,000.
In the Discovery and Validation phases, inconsistent startups have 75 per cent more paying users. In the Scale stage, consistent startups have a 50% advantage.
Startups Fail for 6 Reasons
The following are the most prevalent reasons for failure, based on our extensive interviews with 80+ failed startup founders, which you can read in full in our Startup Mistakes article:
1) Issues with Marketing (56 per cent)
The biggest killers were marketing errors, and the most significant issue by far is a lack of product-market fit. Don’t spend a lot of time and money unless you’re confident that others will desire what you’re selling.
Validate your assumptions fast and inexpensively, and pivot if necessary.
2) Team Issues (18 per cent)
The biggest killers include issues like a lack of subject expertise, a lack of marketing knowledge (and strategy), a lack of technical understanding, and ultimately, a lack of business knowledge.
Team conflict, a lack of enthusiasm, and a lack of availability are also prevalent, although less dangerous.
3) Financial Issues (16 per cent)
Even though more than half of the entrepreneurs questioned did not have a budget for their business, and 75% were self-funded, just 16% blame financial issues for their failure.
This is because testing and validating concepts do not need much money (you need effort). Financial issues mainly affect later-stage firms because you need money to expand an already proven concept.
4) Technical Issues (6 per cent)
Even though most of the businesses examined have some form of technology at their foundation, it is rarely a key killer.
The most common blunder is overinvesting in pricey technology (developer time) before validating marketing assumptions.
5) Issues with Operations (2 per cent)
Operational issues are uncommon among software companies, as evidenced by most of our interviews, and this may not be the case for startups that operate with tangible goods.
6) Issues with the Law (2 per cent)
Frequently exaggerated, and only a tiny percentage of the time the cause of failure. However, tightly regulated areas such as food and banking continue to pose legal challenges.
Failure Rates of Startups by Industry and Sector
Statistics from the Office of Advocacy reveal that new company failure rates are comparable across established firms’ industries.
Other data from the Statistic Brain Research Institute shows how often new enterprises fail after four years in specific industries:
The Information Industry has the most significant failure rate, which may seem unexpected. On the other hand, the information business has a low barrier to entry, and it contains many actual high-risk startups, which may be driving increasing average failure rates.
If your idea or business is more traditional, the figures above should be helpful. There are no reliable sources of failure rates for truly creative tech firms segregated by industry. Nonetheless, this picture from the Startup Genome 2019 study might be helpful. It splits companies into sub-sectors and determines whether the sectors are expanding, maturing, or falling based on early-stage financing and 5-year exits:
- Agtech & New Food
Agtech businesses have a significant barrier in introducing new technology (mainly digital) to a mature, established sector with a limited number of early adopters.
- Blockchain
Blockchain has a lot of promise. However, the reality of the highly volatile and speculative coin market and potential stakeholders’ unfamiliarity with the technology make it challenging to put theoretically solid ideas into effect.
- AI, Big Data, & Analytics
While it is undeniable that AI holds a lot of potential for the future, it is in its infancy, and finding economically viable applications has proven challenging. Several of the most prominent AI startups (such as OpenAI) are more akin to fundamental science research teams than business startups. A lot of the investors in the field are playing the long game.
- Advanced Manufacturing & Robotics
Although there is no official number, industry insiders estimate that 99 per cent of robotics startups fail.
There are several reasons behind this, but the bottom line is that “robotics entrepreneurs are solving an exceedingly difficult technological challenge.”
So, are these sub-sectors the greatest bet for aspiring entrepreneurs?
The startup above sub-sectors have one thing in common: they are the easiest to acquire funding to get a project off the ground (if you have a strong leadership team), but they are also among the most difficult to build an independent business.
The hottest subsectors indicate the startup industry’s overall ideology. They represent the most challenging technological problems, the most significant possibility for success, and the greatest risk of failure.
Frequently Asked Questions
What’s the startup success rate?
As we’ve seen, 90 per cent of startups fail, implying that the success rate for new businesses is roughly 10%. If we examine other, more traditional firms and creative digital startups, the percentage is substantially higher.
Why do startups fail?
Marketing, Team, Finances, Technology, Operations, and Legal are the most typical areas where companies experience challenges that force them to shut down.
How many startups fail within their first year?
According to the Bureau of Labor’s Business Employment Dynamics report, there is a 20% failure rate in the first year. Because most new firms aren’t actual startups, you shouldn’t believe your chances of failing in the first year are just 20% if you’re attempting to do something novel.
What happens when a startup fails?
Failure need not spell the end of the world. You’d be shocked at how many failed company founders are now operating profitable businesses. Another group obtains an excellent job as a result of the project capabilities. Your expertise and chances of success improve with each failed effort.
Conclusion
Hopefully, we were able to dispel some myths about new business startups and failure rates! Startups are risky, yet with significant risk comes excellent potential. Potential not just for financial gain but also for development and invention that might improve people’s lives worldwide. So, don’t let the prospect of failure dissuade you! Dare to be unique!
