I don’t know if it’s possible but I would love to see all these concepts proven by data.
If that's the case, an optimal strategy might be to take as many convex bets as possible, keep secret all the ones that fail, and then once a low-probability bet succeeds, milk it for all it's worth and convince everyone you're a genius. You can then leverage that for significant financial gain from organizations who seek genius-level insights in the future. Eventually regression-to-the-mean makes you lose your credibility, but in the meantime you can pocket significant amounts of cash and invest them in much more stable revenue-generating assets.
A glance at who's been successful since the 3rd millenia started shows that this might not actually be a bad career strategy.
One of the criticisms of psychological studies historically has been that we've been studying mostly abnormal behaviors and that it'd be like trying to determine how a car is built based upon only asking repair shop auto mechanics. Similarly though, I think we need to invert this for business - we need to identify commonalities between businesses that fail more than we need to identify the factors that cause success (the entrepreneurship porn out there is potentially harmful this way despite the many articles on the dark side of it). I think the common factors in what causes failures are fairly static compared to the factors that cause success. This interview is a great example of what was successful at one point in history can totally fail later (much greater planning necessary in the early 90s while now we're focused upon market fit / reactivity today as a trend). My gut feeling is that some kinds of companies are better off sticking to their guns and churning out good product independent of the market trends while others need to evolve.
I’m not sure this is actually true. There’s tons of data from “normal” subjects, though normal here mostly means “average behavior of an 18-22 year old college student.” If anything, psychology would probably benefit from more focus on individual differences rather than commonalities.
I must admit I may be missing some much more fundamentals that are discussed in academic programs for business (like data structures in CS programs) but am curious why they're treated as table stakes for merely talking about topics like market fit and growth projections when engineers do talk frequently about "basics" like essential data structures.
However I would caution anyone to be careful with the type of optimal strategy you outline. Diversifying within reason is good, but you have to deliver real value somewhere along the line. The luck involved in building a successful business does not occur in a vacuum, if you are not focused and prepared, the rocketship won't leave the ground (or worse explode mid-flight).
Those who are more obsessed with the financial or social outcome than the actual job of building a business are the ones you find all glad-handing each other at networking events while the most successful always seem to have (or have had) something more important to do.
When you like people, or just your team, you plaster over their mistakes. If you try to reduce the whole thing to something cynical, people just want to watch you crash and burn. Which is I think where you see the problem with reproducing results. You get a certain number of people who just want to turn the screws another two clicks instead of creating a better work environment where more gets done.
I shared my own personal experience in this article https://thenextweb.com/contributors/2018/12/08/this-is-how-i...
Here's the link for anyone interested: https://www.ted.com/talks/bill_gross_the_single_biggest_reas...
I would go even further, ideas are a dime a dozen but execution is what matters--simply staying alive is the biggest issue.
"Timing" is simply staying alive long enough that you are actually present when the correct timing occurs.