In Jurgen Appelo's Management 3.0 there is a conjecture about complex systems, chaos, and managing or not managing this chaos. This weeks edition of Nature, (12 May 2011) has two articles that are important to the discussion:
- In the News and Views "Degrees of control," Magnus Egerstedt, pp. 158-159
- An article, "Controllability of complex networks," Lui, Slotine, and Barbasi, pp. 167-173.
First, these are not anecdotal opinions, but research on complex networks and their control. Second, they are applicable to a wide variety of domains from biology to social networks. Since Nature is a subscription only, copyrighted journal, I'll provide a summary of the News and Views.
One might expect that social networks would generally be harder to control than naturally occurring systems such as biological networks. But this is not so...
(Network are constructed of) nodes of individual decision makers, for instance people in a social network, ..., or DNA segments in a cell. The edges are the means by which information flows and is shared between the nodes.
The flow of information in the network is what enables the nodes to make decisions or update internal states or beliefs ... The result is a dynamic network, in whcih the node states evolve over time.
Central to the question of how information, injected at certain key locations, can be used to steer the overall system towards and desired performance is the notion of controllablity - a measure of what states can be achieved from a given set of initial states.
Liu and colleagues (the article) found, for several types of network, controllability is connected to a networks underlying structure. ... The surprising result is that driver node tend to avoid network hubs.
The result of this type of analysis is that it is possible to determine how many driver node are needed for complete control of a network.
Let me stop here and restate this idea. COMPLETE CONTROL OVER A NETWORK. The notion proffered in Management 3.0 of self organization and emergent control appears to be flawed in the absence of a domain and context.
One implication of the study is that both social networks and naturally occurring networks , such as those involving gene regulation are surprisingly hard to control.
By contrast, engineered networks are generally more easier to control, which may or may not be a good thing, depending on who is trying to control the network.
So here's the Point
Engineered systems are both robust and controllable. Let's the system emerge in the absence of a controlling paradigm, is likely a bad idea. The Management 3.0 paradigm is devoid of any real assessment of how these networks of people actually interaction, outside of anecdotal and "populist" descriptions of emergent network. This set of articles starts - or restarts - the conversation around how to organize a group of people around creating a solution to a complex problem.
When we encounter a collection of "notions" based on a loose set of ideas and anecdotes, take some time and possibly some non-trivial effort to look into the basis of these notional ideas.
