How randomization helps is by making it much easier to design algorithms. E.g. Verifying a solution is cheap, so proving your random choice is in some class of good choices and making an algorithm that turns that into a solution is still an interesting approach and opens up solutions to things we cant yet solve.
Derandomizing as presented apparently means proving for a few random but careful choices you're in the funnel towards the right solution, or (hopefully) can detect otherwise, and a few transformations or reasonably performant steps produce your solution.