This recent piece on startup failure statistics caught me eye on Twitter first, and I followed the links to discover Startups: Conventional Wisdom Says 90% Fail. Data Says Otherwise. | Fortune.com. Here’s a direct quote from author Erin Griffith:
“I recently found myself carelessly repeating a statistic that I’d heard dozens of times in private conversations and on public stages: ‘Nine out of 10 startups fail.’ The problem? It’s not true. Cambridge Associates, a global investment firm based in Boston, tracked the performance of venture investments in 27,259 startups between 1990 and 2010. Its research reveals that the real percentage of venture-backed startups that fail—as defined by companies that provide a 1X return or less to investors—has not risen above 60% since 2001. Even amid the dotcom bust of 2000, the failure rate topped out at 79%.”
I was happy to see this because I’ve agreed, including here and here on this blog and also here in the bplans.com articles, that failure statistics are bogus. Overblown. Exaggerated. And taken for granted.
What drives the startup failure statistics myth
I’m not so sure about Erin’s explanation of why that occurs. She says, in the paragraph explaining the one above:
Yet the denizens of Startup Land continue to cite the 90% figure because it serves a purpose. It comforts failed startup founders who burned through their investors’ money, laid off staff, and shut down their companies. It supports the startup world’s celebration of failure. “Sure, you failed, but that’s the norm,” the thinking goes. “The odds were against you.”
I don’t buy Erin’s explanation there. She’s too kind. I think the 90% myth is driven by bogus would-be experts who clutter the web and even business publications spouting worn-out startup clichés to bolster their alleged expertise. I think it’s a side effect of our everybody-is-a-publisher society. People can get attention with certainty untempered by experience. I did a rant on that subject here, not that long ago: Bogus experts give bad startup advice.
An important clarification
Although it doesn’t quite support my point, I can’t leave the subject without pointing out that the data we’re looking at there is not for all startups. It’s just about venture-backed startups, which are the cream of the crop. Of course they do better than the average startup. They are the ones that get through the investment filter process.
And this also shows that so much of what we value in information depends on the definitions. What’s a startup? To me it’s a new business of any kind. To many other experts, the term startup applies only to high-growth new businesses suitable for outside investment. So we have to look, with any of these studies, on what they are really studying. All businesses, or just high-end tech businesses?
And then, before we leave the subject, there’s the obvious thought that not all businesses, startups, small business, or whatever, are equal. When you start your own business, if you do, your odds are not the same odds as everybody else who starts a business. Your odds depend on what you’re trying to do, how well you do it, how well you plan and manage, and what resources you bring with you.
Last thought: I can guarantee you that your odds of failure go way down when you run your business with good planning process. Start with a lean plan and review and revise it regularly.
I was thinking of an analogy of falling through the ice. 100% of hockey players who go out on thin ice would fall through. It the measurement and planning before you go out on the ice that prevents you from falling through. Perhaps the business failure statistic should be attributed to the number of new business owners that do not plan correlated with the percentage that fail.
Bryan, thank you thank you, that’s an excellent addition. Seems like a really good analogy.
Scary thought isn’t it, 10% chance you’ll make it.
Martin, chuckling, I like my bottom paragraphs here, in which I’m suggesting the odds are better than that; and that they depend on what you do. It’s not random, like in Las Vegas. It’s risk in almost all cases, but you can determine how much risk. Thanks for the comment.
The definition of a Startup might need to be refined so not to confuse it with the normal time new business, the percentage will change.
Do you think.
Martin, yes, I do think you’re right. They are different animals, the tech startups and normal small business.