Is there a term to describe the tendency to attribute the cause of a bad outcome to a recent event? I've noticed that when something goes wrong, people have a tendency or a bias to associate its cause with a recent event.  The following may not be a great example but here goes.  

Imagine a game of Jenga where players remove blocks from a tower.  Early in the game I remove two blocks from near the bottom of the stack, destabilizing the foundation of the tower.  We have some skilled players so we manage to make it four or five more moves before the tower falls.  Although I destabilized the tower from the beginning, there will be those who perceive that the move prior to the last one was the main contributing factor.

I ask because this is a pattern that I see in my job and I'm trying to communicate it to someone.  We see projects fail because the foundation work done months prior was not of good quality.  Nevertheless, the blame seems to go to the last person who touched it.  I can't help but think there is an established term that describes this psychology and would love to be able to reference it.
I don't know of a single term for it, but what you're describing is, in essence, causal inference driven by "statistics", "co-variation", "co-occurrence", or "contiguity" (the terms are largely interchangeable).

If you're interested, there's a quite in-depth discussion review of theories of different theories of causal inference, including statistical models, here.

I think your example can be tied in quite nicely with "dual process" theories too, which propose two kinds of thinking: automatic, intuitive processes, which are sensitive to things like co-variation, and more effortful reflective processes, needed for more abstract relational reasoning. In your case, intuitive thinking easily makes a causal inference based on co-occurance: 


  "Mark touched the tower, and then the tower fell, so the tower must have 
  fallen because Mark touched it"


while more effortful reflection is needed to construct a causal model involving foundational work done months ago. I don't know of any specific application of this intuitive/reflective distinction to causal reasoning, but I'm sure it's been done somewhere.

EDIT: I've just remembered this paper, which discusses a similar idea, but in "multiple
cue probability learning", a specific kind of causal learning. I feel a little obliged to plug this, because one of the authors is my PhD supervisor.