What should be done when the theory behind a PhD thesis turns out to be wrong? I have a friend who has been working on a PhD dissertation for over 3 years and he is supposed to be wrapping it up. Unfortunately, his thesis involves a complex model and populating the model with hard-to-obtain data. After having finally gathered all the data and plugged it into the model, he is finding that the theory is more or less non-predictive and does not work. In other words, he had an interesting theory, having been tested against the data it turns out the theory is wrong.

So, in this situation what would you do? Just write a dissertation that says, "well four years of research shows that this theory is wrong"?
Why was the theory wrong? "It didn't work" is not the end -- the end is knowing why it didn't work. There are at least two possible answers:


There is some fundamental, obvious mistake at the core of the model that should have been caught a long time ago. In this case, it may be a matter of starting over. It's difficult to produce a paper/thesis if the story is "I made a stupid model and it didn't work." 
There is some previously-unknown reason why the model didn't work despite smart people thinking it would. This is likely an interesting, publishable result. In fact, it could be even more interesting than a paper that just says "we used a model and it worked as expected."


It sounds like the data is valuable as well. Even if it is a matter of starting over again, this dataset sounds like it could lead to a publication or be an ingredient in the new thesis.