It's easy to match reality when you're non-rigorous

Not if you want to make forecasts (= good decisions for the future).

But, when your decisions become very complicated (what startup should I start and why)) , turns out that vague explanation isn't much help. This is when you need rigor.

That's when you need to avoid simplistic models which will lead you astray. Your criterion is still the best forecast. Given the high level of uncertainty and noise I am not at all convinced that the more rigor you can bring, the better.