Startup Failure by Industry(statisticbrain.com)
statisticbrain.com
Startup Failure by Industry
http://www.statisticbrain.com/startup-failure-by-industry
10 comments
It's interesting to notice that 9 of the causes of failure are due to poor financial controlling (as in terrible or absent financial controller/manager). Which does confirm one of my thoughts about startups: they need huge margins to offset all the poor financial planning and accounting mistakes they do. It's not a bad strategy for many, but it is deadly for some. It's a pity given some solid financial controlling advice is not that expensive or hard to get, I believe.
This dataset seems to include all businesses and not just technology startups.
In my experience, those who attempt to start small businesses often learn the hard way of the importance of accounting and financial planning. Can't just run a business out of your personal bank account.
In my experience, those who attempt to start small businesses often learn the hard way of the importance of accounting and financial planning. Can't just run a business out of your personal bank account.
Cashflow forecasting at the start of any business venture is almost always guesswork.
The best defence against lack of predictable income for startups is to simply keep overheads to the absolute minimum. This buys the longest runway and increases the chances of survival.
The best defence against lack of predictable income for startups is to simply keep overheads to the absolute minimum. This buys the longest runway and increases the chances of survival.
Right, but you have to spend money at some point. Once you do, you need to make assumptions on how the future will look and keep track of things. If I assume a monthly OpEx of 100, somebody has to keep track of that number, the worst that can happen is to have an increase to say 120 and nobody noticing or thinking it's worth notice...
For businesses that have to buy in stock cash flow is critical, get that wrong and your revenue can collapse in an instant as suppliers stop shipping.
I'm really interested in the underlying source data and sample groups. Based on the article, I'm unclear if these are actually startups or just small businesses.
From the point of view of most economic studies, there is no difference. For them a business founded for the purpose of making is a startup, be it a plumbing business or an on-demand food delivery service.
if the underlying data source is tight this would be a rather fascinating piece of research...
Education and Health are lumped together? These are vastly different.
So businesses that require you to be extremely well capitalized to be in them (finance, real estate, mining), or are extremely well capitalized through subsidy (education, health, agriculture), are more likely to be in business after 4 years?
Got it.
Got it.
It talks about failure and didn't care to define what that exactly meant? Going bankrupt? Closing down the business with very less profit? What does failure in the 9th and 10th year look like?
+1
If you sell your company after 3 years or get a job that's better than consulting, the business entity is no longer operating - though that may not be a "failure" for the founders and employees.
Meanwhile there are zombies that have been draining founders and burning out employees, yet are counted as a success because the business is a going concern.
If you sell your company after 3 years or get a job that's better than consulting, the business entity is no longer operating - though that may not be a "failure" for the founders and employees.
Meanwhile there are zombies that have been draining founders and burning out employees, yet are counted as a success because the business is a going concern.
> If you sell your company after 3 years
How exactly is that a failure?
How exactly is that a failure?
That's the commenters point. We don't know what data was sourced for "failures"
This information is very vague. I'd be interested to see how they grouped the startups into those categories. For example, FarmLogs is a business in the agriculture industry but the product itself is information/service. Where do you draw the line?
FWIW, this statistics mirrors well my own failure as a startuper. So even if I cannot judge the dataset, it looks at least worthy of attention as a sobbering checklist. Kudo to OP.
Information startups have the highest failure rate, but the capital requirements are lower than, say, mining.
The "statistic" seems to make a point that taking a bet on a strategy and losing is incompetence.
The listed specific pitfalls aren't about taking a bet. They're pretty clearly elements of incompetence. I wouldn't call nonpayment of taxes or living too high for the business taking a bet on a strategy unless that strategy is to fail.
Er, there aren't links to the sources. You can't just take someone else's data randomly, assert as truth, and not show its original form. (unless said original form has restrictions on redistribution)