Startup mistakes: Lessons from failed startups

I think tech problems are under-represented.

The thing about tech problems is that they don't show up as tech problems unless they are really bad. They usually show up in lack of product-market fit, lack of adoption, high turnover, and difficulty with sales and marketing.

For example if you chose Electron for your app and put no effort whatsoever into slimming down what you are running inside, users might decide they don't want to use your app because it uses too much CPU and RAM. If you use a slow database as your SaaS app/site's backend, your site will be slow and users might bounce during trial. If you pick an unwieldy, bug-prone, or weird (a.k.a. hard to hire) technology you might experience a slow development cycle and find it hard to build enough features or fix enough problems.

Most of the time people won't tell you these things. They'll just move on. Some of them are subconscious, like performance issues. The app just doesn't "feel" good, it's not a pleasure to use, etc.

If you are trying to sell shit on a stick, your problem may not be marketing... but you can always blame it on marketing! If your stack makes your development cycle slow, maybe you're not finding product-market fit because you're hiking through the woods with an elephant strapped to your back.

Good tech choices are fundament. They enable everything else to work well. You need everything else of course... good tech alone won't cut it. But the rest of your company's operations are going to flounder if they are not properly equipped or if the product sucks.

Not having concrete examples, but the book 'crossing the chasm' claims, that the majority wont buy from you whatever you have and they need unless they know 2 other companies (succesfully) using your product. Supposedly the step from a few sales to fully tapping the market is hard even if you have great products.

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, more likely, the set of actions) that precipitated the event, the more you rely on memory and hearsay

   3. "The Rage to Conclude"- humans LOVE denouement, to “know”, to have things wrapped up and make sense. But rarely is the world so simple. We try to boil a set of reasons down into one über-reason

So on the factory floor, the people doing the labeling are incentivized to shift the blame and obfuscate their role in the loss. And then the manager is trying to sort through all the noise to identify which set of reasons is the most likely for this loss. There's a lot lost in translation from the "truth" of how the deal was actually lost.

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With this particular article, I categorize it in "content marketing babble": advice that is generalized to the point that it is not useful to me. The Common Lessons section leaves me with general advice but no tractable ways to understand what that looks like in the real world with real constraints and stresses.

IMO, the Lean: validation section could be extremely valuable IFF they supplied hard examples from the failed startup dataset that fueled this article. Like "Here are links to the case studies where the team behind [Closed Company A] felt that they could have spent more time validating before building. This is the featureset that they built prematurely, and here they ponder on ways they might have tested it cheaply"

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All that aside:

I've actually been quite an avid reader of Failory for a couple of months now. I check in every so often to go over new interviews. I think the interviews (https://www.failory.com/interview-failure) are a lot more useful: the format allows for more nuance, more context over the conditions of the business, and more reflection.

I often find myself wanting to ask more questions in-line to the interviewee, kind of like a hyperspecific, morbid Quora question.

[1] I'm co-opting this term from Sales/Marketing lingo. I originally wrote Root Cause Analysis, but I know that RCA has a very specific software definition and set of rituals, so I wanted to

There is both a lot of survivorship bias and probably misattribution of what leads to failures and successes. I imagine a lot of it too is really indescribable, in the sense that a professional basketball player may write a blog post about how to play top-tier basketball, but reading won’t actually make me any better at basketball, nor will it give me the character/physical traits I need to be talented.

Do you have a breakdown of "Common Reasons For Startup Failure" by total funding amount bracket? Is there a trend?