This blog post is about 6 heresies you could do with EA. And in my opinion, this is why EA fails because its too slow to actually do something useful. In any system which EA is needed the details are hard to capture with EA and its tools are too abstract. The post also says that EA practitioners usually fall in love with their framework so much that it becomes framework produced model which is not modeling the system its supposed to model and they should develop something that "works" for them.
It would be nice to have some framework to reason about the system, problem is that how the functionality of the system is in the details of where the code is executed. Usually the models of a system is bound to the physical structure of the system and also that a process forms a module. This is just not simply true, but to know that you have to dig into the code where there are several details which makes out the functionality. There are things like language constructs, code constructs and lack of information which is crucial for the model, but that is only found in how the code is built. And unless we are able to figure that out each time we take a "snapshot" of the system, EA and the tooling will fall short.
For EA to work it has to be a lot more code centric, and it's tools needs to be able to understand code and what its built for, and unless that is not figured out EA will not to able to provide information which could be based on making decisions. I'd say because of this EA is responsible to actually make systems worse because you are not able to make decisions which is reflected by the code but the process instances, which is not good.
There are several other issues with EA related to the inflation of patterns, but thats another post.
Edit: A good view is this video. Simon Brown has a good things going on there.
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