Glen Alleman and a number of commenters contributed to a great thread on math, PM, and complexity (here).
I try to keep the ideas of complexity “science” in mind when planning strategy and its execution. In particular, I have a deep respect for the power of self-organization and the need to create flexible rather than brittle management systems.
However, I’m not sure how powerful CAS really is as a theory, at least w/r/t/ project management. For example, how do its predictions advance my estimation approach beyond what we’re doing w/ probability distributions (e.g., Monte Carlo simulations via Crystal Ball)? To I really need math beyond that to get “good enough” estimates?