Why startups fail, according to their founders
fortune.com
fortune.com
His plane ticket was paid for by the person sitting next to him -- a mutual friend. Jody was supposed to pay him back for the ticket. He never did.
Interesting that his "business failures" are the causation for a trend, as his businesses were never intended to succeed in doing anything other than separating investors from their money and trying to stay one step ahead of what inevitably caught up with him. People seem to think that he was overly optimistic and just bad at making a business succeed. That might be true; I do not know what he ever actually intended. I told him several times that in order to get one of his former businesses to succeed he would have to spend money on certain key pieces of infrastructure. He refused, saying he'd spend it later. What I didn't know at the time that he wasn't being simply unreasonable. The money was already gone. It just didn't say that on the balance sheet he was showing to those who worked with and who he approached asking to invest.
http://www.businessinsider.com/jody-sherman-ecomom-2013-4?op...
1) make a product that people want (vs. no market need) 2) attract investors (vs. ran out of cash) 3) media virality (vs. poor marketing) 4) perfect timing (vs. product mis-timed) 5) have clear distribution to market 6) lots of luck
#6 is not mentioned at all in the article and is probably one of the biggest factors.
Luck is a huge factor in success, and it plays into all those things in very direct ways. I've been involved in three failed startups (and one successful consultancy) and seen all those factors play out.
Timing and making a product enough people want (and are willing to pay for) are the two areas where luck plays the biggest role. Market validation is a huge issue for new technology, and it's surprisingly easy--with the best market intelligence you've got--to build something that not enough people want (yet) to make money.
And not all markets allow fast pivots or particularly small MVPs. Sometimes you don't know it isn't going to get picked up until it's too late to change course. In other cases there is simply no way to know if you should take a fairly good offer today and cash out, or not. It's easy to point to cases where founders turned down good offers and went on to make large multiples of them, and cases where founders turned down good offers and went broke.
It would be a very valuable exercise to gather up cases like that and present them in a business school context. My bet is that no one would be able to consistently make the right decision based on the information available at the time, which would make the role of luck unequivocal.
Market fit should be worked out ahead of the team by the cofounders. The great team will contribute to it and over time everything evolves. Should the market shift fruit when you have the team, team transparency will help everyone steer the ship in a different direction. Otherwise the company will run out of cash chasing the founders fixed mindset.
It was a great product, delivered on time. It fulfilled a genuine need and it did it better than anything the competition had to offer. But the market wasn't there to sustain the company, and there was no reasonable way to know that far enough in advance to do anything difference.
This is the essence of luck. People hate that, but it's the truth.
So basically to your point. Market fit is pivotal to the health of a startup.
I hate all of that Taboola link bait 'recommended for you' crap. Does that really make money for the website? I can't imagine it would, at least not much.
People need to take the Facebook movie this seriously, the same way many startups take the Steve Jobs' ideology.
I only say this because of a recent video series I watched from Stanford (I think) where the speakers, all successful founders, drilled in that idea from the get-go.
It's not a contradiction. Refer to the chart in the article: http://fortunedotcom.files.wordpress.com/2014/09/unknown2-e1...
Luck can be an important component, however, it doesn't mean it's not super-easy to identify an immediate cause of death in the absence of that luck. For example, let's suppose that you literally have to win a lottery or none of your sources of funding will close. (Remember, we are defining this as a lottery for this hypothetical mental exercise - I don't think it is one.)
Now, there is luck, for example the must-have round closing days before money runs out. That is luck. (In point of fact this is actually reported by some founders - the same ones who declare how lucky they were.)
And on the other half of the spectrum, article shows 30% of startups reporting dying due to running out of money. So in the other 70% of cases the startups either: got lucky to close their round; or had no trouble closing their round; or didn't need it. In any case in 70% of cases, running out of money wasn't the reason they died.
So even though we used a simplified model that you have to win a lottery to get funding, we can still see that it results in some people reporting they were very lucky to get funding at the last minute, however the cause of death in 30% of cases remaining "running out of money."
Likewise, some companies will chance on a product people really, really want, and pivot into it. Meanwhile, "No market need" kills 42% of startups.
So there is no contradiction. You can have three groups of companies in each case:
(1 funding):
Group 1: No problem closing funding. (Or don't need it.)
Group 2: Nobody wants to fund and would die, but miraculously
closes a round just in time. Reports being super-lucky.
Group 3: Tries to get into Group 2 after realizing they're not Group 1. Fails to do so.
They die and report "Running out of money" as cause of death.
After this point, who do we hear from? We hear from 3 in the present article. We hear from Group 2 - very frequently - after they report how lucky they were. We also hear from members of Group 1, who report not having trouble closing their funding rounds.Now let's look at market fit:
(2 market need):
Group 1: No problem with product-market fit.
Facebook would be an example, Dropbox another.
Group 2: Building wrong product, nobody wants it.
But gets super-lucky and chances onto a market niche and pivots into it.
Group 3: Building wrong product, nobody wants it.
Does not get super-lucky and accidentally pivot into something people want.
So, we hear about Group 2.3 in this article. It accounts for 42% of deaths. We also hear frequently about Group (2.)1 and sometimes about Group 2.2.It's rarer to hear about Group 2.2 though!! (Much rarer than in the funding example where good ideas were really lucky to get funded at all.
So since we hear so frequently about groups that were really lucky to close their funding for a good idea, but more rarely about groups that were really lucky to identify something people actually wanted, while building the wrong thing, it stands to reason that Building the Right Thing is less based on Luck than funding is.
I'm not 100% sure of this reasoning though.
However, from the analysis above you can clearly tell that simple luck is kind of orthogonal to the points raised in the article. :)
I continue to believe that luck is the meeting of preparation and opportunity - that doesn't guarantee you good luck or business success, but it sure beats building a business in a basement without talking to the market and hoping you get it right!
A few things to note are that it seems like a few of those items could be combined into the same general problem in a failed startup: Not the right team, poor marketing, poor product, and disharmony on team/investors could potentially be related.
Another point is that these are obtained from self post-mortems by founders, whereas if the data were obtained from employees or investors, you might get a different story.
https://www.cbinsights.com/blog/startup-failure-post-mortem/
This has been a test.
Based on our research, we've found that startup founders who fail to notice that this list adds up to 300% have startups that will also fail.
Your user ids have been added to the investment exclusion list.
Thank you for participating.
Likely the servey was, "list 3 or more reasons why your startup failed," and then the top three where used in this list. This can be used for voting and ranking but deriving a percentage is inappropriate. Someone's 3rd choice may be only 1% of the reason they think they failed. there is no concept of relative percentage between the three choices of a single respondent.
If anything it is the set of three answers the respondent considers salient, in which case they are inseparable. They might have answered quite differently if they where asked "what is the single most important reason your startup failed."
Which is what this article claims it is listing.