Great post/thread on Mathematics, PM, and complexity

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?

How much complexity theory can we apply in IT?

I’m fascinated by complexity theory and attempts to apply its insights to the software business.  If you’re interested in those topics you could do worse that to add two bloggers — Jurgen and Bas — to your newsreader (don’t forget about Crossderry). 

Both touch on complexity regularly (Jurgen’s latest here, Bas’s latest here) and they’re clearly big fans of the theory and its implications.  I agree there’s much that’s applicable, especially the concepts of iteration and feedback, which can even be used in “waterfall” approaches (here and here).  My academic background makes me especially sympathetic to the limits of central planning (start here re: Hayek).

That said, I’m not sure we can rely on self-organization for everything.  The most effective models of complex adaptive systems are derived from simple rules that generate complex phenomena.  This approach is mimicked effectively in agile, iterative, and other rapid development techniques (list of SW methodologies here).  Simple feature lists, regular interactions with stakeholders, short cycles, many versions of usable work product, etc. can generate feature-rich and useful applications.

However, the scalability and stability of these applications is often problematic.  IMO, this result is to be expected given the evolution of complexity among living things.  We like to point to complex creatures and structures — e.g., human brains — to support applications of complexity theory. 

But do we remember that most life is still very simple (about half of the biomass is microscopic)?  Also, aren’t complex creatures the ones that have had the spectacular denouements over the eons?  Betting on self-organization isn’t always a winning bet.  As I said, I instinctively like leveraging complexity concepts, but we must remember that they cut both ways.

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