What Kills Startups? A study. | Hacker News Reader

What Kills Startups? A study.

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98 pointsentangld42 comments

"Herrmann said that the team’s research found that of the 90 percent of startups that fail, 70 percent scaled prematurely"

They must have had a strangely biased sample. Since the Bubble (when it was common) I've seen few startups do that. What kills startups is making something users don't want.

Maybe by "scaled prematurely" they mean "started hiring and spending lots of money before they made something people want."

Edit: This wasn't intended to be snarky, I was being serious.

I assume that's what he meant, but it is comparatively rare. Nowadays most failed startups die small.

The way we've defined premature scaling, "making something users don't want" is included. For example, on the customer interaction metrics, which is what is used for "actual stage" a startup would be in the discovery or validation stages (stage 1 or 2). On the behavioral stage if they're making something people don't want, they're probably focused on streamlining their product or making it more scalable, which is a stage 3, or efficiency stage action. This would cause the startup to show up as a Behavioral Stage 3 / Actual Stage 2 and be labeled as premature scaling, just not the drastic kind, that for example WebVan exhibited — "Behavioral Stage 4 / Actual Stage 1". They had a team that was completely scaled up without even having shipped their product.

If I were you I'd just use words in the way they're ordinarily used.

:) - I guess we can still improve on simplicity.

If this is meant to be academic research (and I get the feeling it is), then it's unlikely they'd be able to use words as they're ordinarily used. Terms used will have to be clearly defined and stated in order to avoid confusion and misinterpretation (unless you're suggesting that such definitions already exist).

Unfortunately, this doesn't make it easy to discuss things outside the research field.

I'm not sure how else they could term it if they want a consistent label for all stages. Colloquially, it would be "they got too big for their britches", but that doesn't come across well in a study.

It would probably be better, though, to have phase-specific terms. It would probably make it easier to identify with each phase.

Given the mention of Webvan and the sheer number of startups in their study, it would seem their sample group does include a significant cohort from the Bubble. Trying to derive generalized rules governing startup outcomes is tough when those rules inherently keep changing.

Webvan is the first example of failed startup in Steve Blank's Four Steps to Epiphany. I think Startup Genome project was heavily influenced by Blank's book, so it might just that, a familiar example, not a data point.

That's correct. All startups in our dataset we're at least active between Feb 2010 and May 2010 when we started collecting data.

I'm thinking selection bias was at work. They surveyed startups they could find - how? VC lists? Bankruptcy filings?

How many startups failed that never got on their radar? Most?

I skimmed the report, their "methodology" link, whatever other links worked, and I did not find out how they found the startups they measured.

I regard startups that cannot get funding beyond friends/family as hobbies.

Using the term "scaling prematurely" is leaving the report open to misinterpretation: Since "scale" is one of their stated startup lifecycle stages.

In the report they use the term "consistent" which is less confusing and more descriptive of the symptoms of the "predominant" of failures. From the report....

"Consistent startups keep the customer dimension, the primary indicator of progress in a startup, in tune with product, team, ﬁnancials and business model. This means that each dimension progresses evenly compared to the others. Inconsistent startups have one or more of these dimensions far ahead or far behind the customer dimension. Premature scaling is the predominant form of inconsistency, but its much rarer opposite, dysfunctional scaling is also possible, although it’s not covered in this report."

Making (something users don't want), or not (making something users want)?

i.e. is failing to make anything at all a substantial portion of the failures, in addition to successfully making the wrong things?

They're both common. Some people build something elaborately wrong, others just don't get enough done.

one we call premature scaling, the other we call dysfunctional scaling ;) ... btw. @pg did you read any of our reports?

Disclaimer: Purely anecdotal evidence ahead.

I've worked for two startups that failed and did consulting work for another one that idled lifelessly while the founder refused to admit defeat. In general, aside from having a clunky, ugly product that didn't really solve a genuine problem, I also noticed another trend:

The founders were too stubborn to recognize or listen to their users (if they had any). The word "pivot" was not in any of these founders' vocabulary. We'd look at the data, and see users not touching these new features we added and instead the founder(s) just shrugged and said, "No, the users just aren't using the product correctly".

No, you idiot. Your product sucks.

I, along with a few other employees tried in vain to convince the founders that we needed to stop adding useless features and start listening to the data, and the founders just decided to try to convince the users to use the app the "correct" way instead.

This, in turn, led to employees (and even co-founders) basically just giving up on trying to convince the founder/CEO of a need to pivot, so in essence the employees had already given up on the product. And when your employees (and cofounders, ffs) have given up on the product, you've already lost.

interesting read.

The study indicates premature scaling is the number one cause of startup failure. Y-Combinator's results seem to indicate the number one cause of failure among its startups is kind of the opposite: the startup just kind of peters out, and the founders go work on something else.

I assume this is a result of selection bias on both sides: Y Combinator only funds extremely small startups (generally 2-3 people), and this study likely (though I'm having trouble verifying) only includes startups that got beyond this phase. Does this sound reasonable?

Hey Max here...one of the authors of the study,

Our study contains startups that are in stages across the board, (Discovery, Validation, Efficiency, Scale).

While many of the YC startups don't reach the Scale stage, and maybe don't scale up their team or or raise too much money, they can still prematurely scale the product by over-engineering the product and not doing enough customer development. There are more nuanced case of premature scaling that are also discussed in the report.

I was going to post here asking what sort of scaling the report was talking about since asking here would be faster than registering to get the report. Now I have your answer, but the answer is intriguing enough that I'll probably go ahead and register.

It's an interesting study, no doubt. However I keep wondering if you can really judge a start-up's chance to succeed without taking the actual business idea/concept as well as the entrepreneur's personality into account. Since it's very hard to operationalize those, I do understand that you refrained from including it. I've just got the feeling that the quality of the business idea and the entrepreneur's traits might be a pretty powerful confounding variable for what you examine. Therefore it seems necessary to me that these variables are being controlled somehow. I'd like to illustrate that issue. You name premature scaling as the most important factor for start-ups to fail. While this conclusion might not be wrong on the one hand, it may be an illusion that the premature scaling is the actual reason for failure. As an example, premature scaling should be very likely to happen to a "megalomaniac" entrepreneur who just overestimates his business idea's chance to succeed or its growth rate by far. If megalomania is in place at that stage, one have to assume that it also was when the entrepreneur founded his business - by highly overestimating a crap idea who wouldn't have deserved to be turned into a business. In this case, the business' failure wouldn't have been caused by the premature scaling (although it seems to be since that's what you were looking at) but by the entrepreneur's tendency to overestimate the quality of his idea. That said the premature scaling is just another outcome of the true, underlying reason for failure - but not a reason itself. It's just an example, but it might show that it's risky to name your variables as crucial factors for failure as long as you don't control what the business is based on in the first instance: the business idea and the entrepreneur's personality. What are your thoughts on that?

The initial idea isn't that important. Entrepreneurs change their idea all the time. In the report we show that consistent companies or ones that scale properly, are more focused on discovering whether their idea makes sense where as companies that scale prematurely are more focused on validating that they are right. And as far as personality, while it's an interesting variable to look at in the future, in the end of the day we just look at whether the company produces results regardless of their predisposition. It's also common wisdom that there are many different kinds of entrepreneurs that have been successful.

I see your point - however I still think that the company's predisposition is too important to be left out. In this spirit I suspect premature scaling to be a dependent variable (instead of being a first-level factor).

Warning: I filled out 80% of this, stopped for a call then hit the back button accidentally when I got back. All my input seems to be erased and I'm not spending another 20 minutes on filling it out again to find out what happens at the end. (I just submitted this bug to their uservoice).

"98% of startups fail because 98% of startups are unnecessary. They're trying to solve artificial problems." -Joey Pfeifer

The question is whether the founders are capable. Do you think 98% of founders are incapable of creating something useful?

My experience is that you're not going to have the problem as clearly defined as you thought in the beginning. If you have a capable team and a flexible strategy you can and must redefine the problem you're trying to solve as you learn more about the domain. I would add that as a form a failure in startup culture: To get so enamored with a perceived problem and your proposed solution as to ignore new evidence that should alter that first impression. Sometimes the new information leads you to incremental or 'attainable' adjustments and you adapt and move forward, sometimes you need to pull the ripcord and go back to the drawing board.

Today I read an article with the headline "How to Pick the Right Idea for Your Startup." That right there epitomizes exactly what is wrong with startup culture.

Don't have an idea? Don't have a startup.

Ideally, problems could be solved and ideas implemented without the need to form a company, get funding, or turn a profit. Those are simply (often optional) measures that must be taken to help realize the end goal.

Don't have an idea? Don't have a startup.

I disagree with that. Some of the better startups we've funded changed their idea completely during YC.

It's the founders that matter, not the idea. So I'd say instead: if you're not the right sort of person to start a startup, don't start a startup. But of course that is a complicated matter to decide because (a) people often don't know if they are the right sort of person and (b) people change.

So, why not recruit small teams of awesome founders -- comprised of the right kind of people -- and "assign" them ideas?

We already do, kind of. We know that a significant fraction of the groups we accept will change their idea, and that we can contribute as much of their new idea as necessary.

Sometimes we even tell people when we accept them that we'll accept them if they do something different. Greplin was one of those.

Reddit is a more well known example. Do you know what the original idea by the founders was?

Ordering fast food on cell phones.

"How to Pick the Right Idea for Your Startup."

For some people, the issue may not be that they don't have an idea, but they have a few and need to choose the right one to push forward.

Paul Graham's version on what kills startups: http://www.paulgraham.com/startupmistakes.html

Only the startups that solve real problems are able to survive. As a startup you should answer the following questions: 1. Would you use your own product? 2. Would you pay for it?

If the answer to both the questions is a BIG yes, then you have a solid product and a good chance to survive.

And

3. Are you the only one?

I think another major point that wasn't discussed in the post is that the startup world is a rocky one. You might be full of confidence in your idea one day, and then the next day you feel your idea is garbage. It's a roller-coaster ride, and not everyone can deal with that. Especially until you have users that are signing up for your service, it's really just your own personal opinion, you need validation in an idea to continue to give you the confidence to pursue it no matter what your opinion of it at the moment is

"A core feature is something that is required for your service to deliver value. For facebook a core feature is the ability to friend people. An email notification from facebook that someone sent you a message is a nice to have but not a core feature."

Is it a joke?

Without email notifications Facebook would never grow to any meaningful size (if at all).

I'd use this product if the company name was not a required field.

Petty quibble. Save it for https://startupgenome.uservoice.com/ — and note that if your company doesn’t have a (working) name yet, then you’re too early stage to see much benefit here. (If it’s a privacy issue, fake the name.)

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