We see this same type of thinking when dealing with all sorts of other complex, multi-dimensional systems. Economics, for instance. There are a huge number of people who think economies work in this same linear fashion. Or managing large groups of developers.
In some systems that are becoming more complex, such as avionics systems for large airplanes, it's getting to the point where the old root cause analysis methodology is still being used although it's getting less and less applicable (I'm speaking specifically of the crash over the ocean of the Air France flight, but there are other examples)
Our minds desperately want to live in a world with clear causality. Do X and Y will happen. When the world doesn't live up to our expectations, many times we just get out a bigger hammer.
Looking at this problem solely from a philosophical standpoint, it looks like there is a powerful argument in place for tiered systems to have some sort of distributed goal-seeking self-programming (machine learning), especially when dealing with large numbers of identically programmed/configured computers. That way the same combination of obscure causes wouldn't have such a disastrous multiplicative effect. Would be cool to chase that down further sometime.