In general, the underlying idea is: each system has its own critical point. If I know where it is, I hit this point and destroy the whole system. If I do not know this, I will have to go on hitting different components of the system until I accidentally hit the critical point. The more components I damage, even without hitting the critical point, the closer is the moment when the system disintegrates.
And there is a certain connection between “q” - which is the percentage of component interconnection - and “Q” which describes the probability of the whole system collapse.
So what does this formula tell us? In case the damage level of the components (q) within the system is 50%, the system will definitely stop functioning. There are simply no systems capable to withstand the malfunctioning of half of its components. In case q is 25%, there is still an 80% probability of its falling apart.
I’ll buy that one could make this sort of assessment of an electrical network or a water distribution system or an oil pipeline network. But a dynamic network of organizational authorities, human relationships and commands? I think we’d have to generalize away all the interesting content to make such a comparison.
Also, there are obviously assumptions about the underlying the network topology behind the above calculations. I’d be fascinated to learn what they are. Maybe when I read the whole thing I’ll find out.
And there is a certain connection between “q” - which is the percentage of component interconnection - and “Q” which describes the probability of the whole system collapse.
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| Fig. 4. The Probability of System Collapse |
I’ll buy that one could make this sort of assessment of an electrical network or a water distribution system or an oil pipeline network. But a dynamic network of organizational authorities, human relationships and commands? I think we’d have to generalize away all the interesting content to make such a comparison.
Also, there are obviously assumptions about the underlying the network topology behind the above calculations. I’d be fascinated to learn what they are. Maybe when I read the whole thing I’ll find out.
