From Social Networking to Swarm Intelligence

A new area of research called "complexity science" embraces the notion that an ant colony and the human brain, the stock market and Facebook all have something in common. All are complex systems, basically huge networks made up of individual components whose behavior is difficult to predict. Kathleen Ryan O'Connor reports on Bioteams and Research from Binghamton University NY.

From Social Networking to Swarm Intelligence

In terms of Bioteams Kathleen writes:

"It is exactly that rapid-fire change of today's business climate that has shown the pressing need for a new framework, said Ken Thompson, a United Kingdom based expert in the area of bioteaming, swarming and virtual enterprise networks and teams, which draws heavily on the understanding of complex systems in nature. His most recent book is Bioteams: High Performance Teams Based on Nature's Most Successful Designs".

Traditional business teams rely too heavily on a single dominant structure - command and control, also known as individually led teams, he said, drawing from the military. Such an approach "served us well in the era of mass production when costs, consistency and compliance were everything," Thompson said.

But that model falls well short in today's world full of "networks, dynamic alliances, virtual collaborations - where agility, innovation, added-value and responsiveness are king," he said. "We urgently need to find a new model which recognizes that organizations are not predictable systems, like clocks, but unpredictable ecosystems, like living things. The natural place to look for this model is nature itself with its numerous examples of self-organizing systems and teams in ants, bees, dolphins, wolves, geese and many more."

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Predictably Irrational teams

Predictably Irrational teams
Teams, networks, groups and their members behave in an irrational way but quite predictably so. A good team leader will understand this and use it to everyone’s advantage. One key point is to knowing each team members motivations and whether they are operating in “social economy” or “market economy” mindsets.

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