Apart from the God-awful layout, the article is pretty light on anything useful or actionable.<p>> I need merely two variables [...] resulting in a simple yet accurate model.<p>It's accurate-enough, but not <i>accurate</i> accurate. This is why things like quantum gravity are being researched. Maybe I'm looking too deeply into this analogy, but I think it's a really bad one.<p>> In highly complex systems such as business, things like butterfly effects can cause massive distortions rendering our models flawed.<p>Most businesses fail due to a lack of product-market fit. This has nothing to do with chaos theory or initial conditions. In fact, I'd say if you have product-market fit, the market tends to be very lenient of initial conditions.<p>> In order to perfectly predict the weather, you’d need incredible amounts of data and an equally overwhelming number of data points and then somehow synthesize that into an accurate prediction.<p>I'm pretty sure that we're still not sure if you can even actually predict the weather -- like, ever (we aren't sure if Navier–Stokes is smoothly solvable in 3D). All these physics analogies are just shallow and inaccurate.<p>> It’s easy for the takeaway to be human behavior is difficult, business is complex, all data is meaningless, we can’t apply a scientific process at all, let’s wing it. And while there are people who lean heavily on intuition (Gary Vaynerchuk comes to mind) I believe if that’s the takeaway, the pendulum has swung too far out of whack.<p>I'm not sure why this is "out of whack" -- to me, this seems like a perfectly valid strategy. As I get older, I value intuition more and more. There's a reason Warren Buffet's moniker is the "Oracle of Omaha."