In my prior blog post, I talked about Complex Adaptive Systems. These are adaptive, non-hierarchical, self-organizing systems, with robust emergent properties, where simple rules can lead to very interesting emergent results.
Complexity wasn’t a convenient reality given managers’ desire for control. The promise of applying complexity science to business has undoubtedly been held up by managers’ reluctance to see the world as it is. Where complexity exists, managers have always created models and mechanisms that wish it away. It is much easier to make decisions with fewer variables and a straightforward understanding of cause-and-effect. Here, the shareholder value philosophy, which determines so much of how our corporations operate these days, is the perfect example. Placing a rigid priority on maximizing shareholder returns makes things clear for decision-makers and relieves them of considering difficult tradeoffs. Of course we know that constantly dialing down expenses and investments to boost short-term margins inevitably damages the long-term health of the company. It takes a complexity approach to keep competing values and priorities and the effects of decisions on all of them in view — and not just for management, but equally for investors, analysts, and regulators.
Complex Adaptive Systems consists of A group of heterogenous agents. Bees in a hive, investors in a stock market, neurons in the brain and ants in a colony are some of the examples of agents. The agents interact with each ...
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