Dataflow framework for global analysis: Why meet, then apply?
It's the classic precision/efficiency tradeoff. You can, in fact, move the meet outside, since $f(x \sqcap y) \sqsubseteq f(x) \sqcap f(y)$. A canonical example of where this makes a difference is in the following constraint-propagation problem:

IF b
  x = 1
ELSE
  x = -1

y = x*x


The Dragon Book's suggestion will compute $(x=1) \sqcap (x=-1)=\top$ before evaluating $x*x$, and will thus not capture that $y$ is a constant. By computing the meet after (twice) evaluating the multiplication, yours will. What you have effectively done is added a small amount of path-sensitivity, for a small price in efficiency. You can continue down this path arbitrarily. Two steps of this analysis may compute $f(f(w\sqcap x) \sqcap f(y\sqcap z))$. Your suggestion would instead compute $f(f(w)\sqcap f(x))  \sqcap f(f(y) \sqcap f(z))$, but you can take this farther and increase the path-sensitivity by computing $f(f(w))\sqcap f(f(x))\sqcap f(f(y)) \sqcap f(f(z))$. The fully path-sensitive MOP (meet-over-paths) solution is undecidable. The Dragon Book's algorithm gives an MFP (maximal fixed point) solution, which safely approximates the MOP. You've simply refined the approximation a bit.