Business Advice Plagued by Survivor Bias
blog.asmartbear.com
blog.asmartbear.com
It's one reason to pursue 'smaller' opportunities with lower variance of return expectations but higher median returns -- for example many niche businesses -- than industries with gigantic return expectations. The latter attracts far more entrants, and while somebody gets rich, the median player does not. But this isn't clear to new entrants because of survivorship bias.
Somewhat related to this is the data availability bias. Big opportunities tend to have much better data sets, and so are easier to study and receive more attention. Many niche industries are closely private and are smaller, so do not have much publicly available data, making study difficult and attracting less attention. Therefore like moths to light bigger industries receive more study and more entrants even though their median expected economics are worse.
This neatly encapsulates much of my current business strategy.
He's publicly claimed to be able to double a million dollars in a year with this approach (it won't work for his $40+ billion, because there aren't enough under-researched stocks to buy that are also bargains).
Am I the only one who regularly reads blog posts by an entrepreneur analysing how he's failed and what he would do differently next time? They pop up on HN quite often.
In general I think it's fair to say that the more popular blogs and books about startups talk about successes rather than failures, so I'll defend my general point.
I did take some license in how I stated it, and thanks for pointing out that it's too harsh and that there ARE good sources of info like that.
But yes it's true there's lots of good material on these subjects for those who want to explore further. Hopefully my piece whetted your appetite -- it's not the final word!
When you try to draw lessons from success during downturns, the lessons are very different, and yet most thought leaders come from bubbles. This deeply effects the quality of the advice out there - most of it comes from people who are to some extent unknowing products of bubbles - but who attribute all of their success to actions they took that have universal applicability. When it often ain't so.
For this reason, for me, 'startup credibility' goes up tremendously when it comes from a serial entrepreneur, or from someone that has actually built a cash-starved company to success during a downturn. "What can I do with very little?" and "What can I do if it is possible to raise $1 million?" are fundamentally different questions - and the same person isn't necessarily going to be skilled in both situations unless they've demonstrated that ability.
Whereas this comment - it has the legitimacy of coming from a complete failure :D
Finally... if your community leaders are state employees that can't say anything negative in public... you really need to be aware of that before you take their optimism at face value. Take to time to query them in private, to find out what they actually think. It might save you some mistakes and some grief.
I remember at one point this guy Richard(?) Kiyosaki had a book "Rich Dad, Poor Dad." In it, you basically found out that Kiyosaki was (a) lying his tits off or (b) a terrible investor. You found out that he'd been bankrupt, and had run several companies into the ground. That he invested in mining companies in Russia whose value would swing 50% up and down from day-to-day - but that this didn't bother him... Wacko.
Yet, somehow, the book was a total phenomenon and made the guy huge amounts of money.
My own article shows that advice from people who HAVE been there (like me) is still suspect, but at least it's MORE interesting than people who have ONLY failed.
Failing, learning, and then succeeding just feels like a better place than just failing, SAYING you learned, and then teaching.
I've heard a lot of startup founders talk about a lot of startups, and only Marc Andreessen (of Netscape fame) both realized and admitted to the large role luck nearly always plays.
So forget In Search of Excellence. Try books like How To Be a Star at Work, which is based on a pretty rigorous study of employee productivity.
And Harvard Business School Case Studies are meant for teaching, and their function is analogous to science textbooks that leave out all the dead ends and fruitless research for pedagogical reasons.
Such a brilliant piece of lateral thinking - thanks for sharing.
So the trick is to separate the 'accidental' features of successful businesses that don't increase their chances of success from the 'essential' features that do.
I wish the article went into how one might do this...
Another example is when evaluating various corporate traits against stock market performances, many people will choose a list of companies that exist today and then study their history to identify correlations of various traits. This omits those that no longer exist today, and it is a common problem among, for example, beginning hedge fund equity analysts. Instead, one should study the cohort from a random sample as existed at the beginning of the study, not at the end, and then study their performances from that point forward.
Select both successes AND failures. Where they seem similar, those things may not teach us much. Where there is a pattern shown ONLY IN ONE SIDE (more or less) there might be a lesson.
I have a fear that there's isn't a lot you can do to guarantee success, but I admit this is just my feeling, not based on any facts or stats.