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Startup mistakes: Lessons from failed startups

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Re: Startup mistakes: Lessons from failed startups

#71
post #14

Are these really "mistakes" or are they just the random process of value discovery, which naturally involves a lot of failures. Finding product-market fit is not something you can engineer with perfect foresight. You raise money, you build something, and then you have a limited time to see whether your hypothesis about the market was correct. Often, if not most of the time, you fail to get the fit you need in order t…

This is extremely well put

-> You raise money, you build something, and then you have a limited time to see whether your hypothesis about the market was correct. Often, if not most of the time, you fail to get the fit you need in order to succeed.

A lot of people will try to counter it

However, that is REALLY what it comes down to

we have a HYPOTHESIS about the market. A product that we think will win/succeed/do well

The Market Always Wins

It either accepts your product (your hypothesis was correct, or became correct by the time you launch your product)

or it rejects your product

Re: Startup mistakes: Lessons from failed startups

#72
post #14

Are these really "mistakes" or are they just the random process of value discovery, which naturally involves a lot of failures. Finding product-market fit is not something you can engineer with perfect foresight. You raise money, you build something, and then you have a limited time to see whether your hypothesis about the market was correct. Often, if not most of the time, you fail to get the fit you need in order t…

> Finding product-market fit is not something you can engineer with perfect foresight. I think the larger problem is that is marketing is near ignored and not just by engineers either. Not many people want to talk to potential customers or users to see if there's product market fit, so they don't talk and listen to anyone outside of the friends and their team which is a huge mistake when they just go ahead and build.…

talking to potential customers and users about product market fit

is not a given it will work

Making a product based on your experience of a market - 25% chance it works out (of which 5% chance it will become a big company)

To that, even after talking to customers

you are only taking it to 30% chance it works out, and of which 7% chance it will become a big company

*

your hypothesis is based on data points

hopefully things like actual experience in the market

market research

seeing what sells

seeing what doesn't sell

*

Customers and users are just as likely to give you bad data (of what they THINK they will buy) or impractical data (something that benefits them and doesn't benefit you)

It only adds a few percentage points to your likelihood of success

on the other hand - seeing what customers actually BUY and SPEND ON, that has a lot of value

However, even that is a piece of the puzzle, and not the solution

Re: Startup mistakes: Lessons from failed startups

#73
post #42

I really hate those kind of content. Would you listen to someone who built a wall which collapsed ? nope But you will tell me, if I can prevent the mistakes other made I will go further than them. Well I'm not so sure, for any mistake that someone thought they made there will be another person who identify this mistake as something which made them succeed. These kind of articles are just porn for people who are not p…

> I really hate those kind of content. Would you listen to someone who built a wall which collapsed ? nope

What if you knew that 90% of the walls built collapses. Would you listen?

If you just listen to the 10% that achieved it, it just a matter of putting more hours: Now you are in survivorship-bias land.

Yes, we all hate that success is a combination of talent + work + luck (aka random stuff we don't know and don't control).

> These kind of articles are just porn for people who are not putting enough hours

there is also success-porn.

Re: Startup mistakes: Lessons from failed startups

#74
post #42

I really hate those kind of content. Would you listen to someone who built a wall which collapsed ? nope But you will tell me, if I can prevent the mistakes other made I will go further than them. Well I'm not so sure, for any mistake that someone thought they made there will be another person who identify this mistake as something which made them succeed. These kind of articles are just porn for people who are not p…

Sure the first 65% is work hard. But guess what? The last 35% is a much different ask that just does not succumb to that same hammer.

As the immediate parent implies, wall building is not all or nothing. Even in statistically controlled manufacturing processes there is std deviation. Not learning from mistakes is itself a kind of arrogance. In fact the preferred model is neither arrogant rejection or passive adoption. To use an a sort of Bhuddist analogy, we listen carefully and extract the gold from the gold+useless ore in the wisdom we hear and refashion it into our own art. This requires decent teachers (suppliers of know how) but also decent students who are interested in real learning not passive regurgitation. Making our own art is demonstration of mastery and of appropriate internalization. It avoids the silly extremes of man as an island and man as an empty if pious vessel to be filled with rhetoric that we can grandstand on.

Those of us in profitable and large organizations will see the same truths about market acceptance and customer approval in a modified way: often our organizations are too sterile and inward looking. Losing the customer starts slow but in that last quarter or two accelerates fast often with a profound finality to it.

Re: Startup mistakes: Lessons from failed startups

#75

One of the big issues I always find with "Closed Lost Reasons"[1] like this is that it rarely captures the truth accurately. It misses the truth in a couple of ways: 1. Deliberate obfuscation by main actors who want to protect their jobs ("It is difficult to get a person to understand something, when their salary depends on their not understanding it.") 2. Continental drift- the farther you get from the action (or, m…

>Deliberate obfuscation by main actors who want to protect their jobs

Sure. There is mal-adaptive behavior, and it's not consequence free.

>rarely captures the truth accurately

Accurately? There's nothing going on in your reply to suggest you have distinguished insight to anything. Throwing out three more modalities of problems amounts to what-aboutism. You have attempted to re-contextualize the original write-up as disingenuous something we see a lot of pointless political wrangling.

The salient question is what we can agree on as to common failure modes, rather than that argue without intersection. No accounting can be complete, and beyond some level of specificity more detail is useless. We're looking for 20% of the causes that explain 80% of the bad outcomes. Think Chaos Report that had a good run in the 1990s.

Re: Startup mistakes: Lessons from failed startups

#76

Earlier quoted context omitted.

> Finding product-market fit is not something you can engineer with perfect foresight. I think the larger problem is that is marketing is near ignored and not just by engineers either. Not many people want to talk to potential customers or users to see if there's product market fit, so they don't talk and listen to anyone outside of the friends and their team which is a huge mistake when they just go ahead and build.…

talking to potential customers and users about product market fit is not a given it will work Making a product based on your experience of a market - 25% chance it works out (of which 5% chance it will become a big company) To that, even after talking to customers you are only taking it to 30% chance it works out, and of which 7% chance it will become a big company * your hypothesis is based on data points hopefully…

With a startup nothing is a given. However talking to your potential customers increases the chances of success because it increases the chances of product market fit. It puts your hypothesis to the test.

Yes, those few percentage points count. Every little bit counts when the chance for failure is high.

I’m not really sure why you’re criticizing my argument.

Re: Startup mistakes: Lessons from failed startups

#77
post #3

This was a surprisingly good read and data-driven. I found it surprising that the top reason for failure was product-market fit followed by team. I would have thought finance (#3) and tech (#4) would rank higher.

Amazon is littered with awesome tech that took 2-3 years to build and launch but failed because there was no market for it. I worked on one such product, a micro payments web service. It took me a while to realize that that’s just how Amazon operates. Carry out experiments all the time, most fail, but the ones who click take off spectacularly. As Bezos says, don’t take Hail Mary bet. Take smaller bets all the time.

What made the micro payments web service fail? If I may ask
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