To provide fast traffic recovery upon failures, most modern networks support static Fast Rerouting (FRR) mechanisms for mission critical services. However, configuring FRR mechanisms to tolerate multiple failures poses challenging algorithmic problems. While state-of-the-art solutions leveraging arc-disjoint arborescence-based network decompositions ensure that failover routes always reach their destinations eventually, even under multiple concurrent failures, these routes may be long and introduce unnecessary loads; moreover, they are tailored to worst-case failure scenarios. This paper presents an algorithmic framework for improving a given FRR network decomposition, using postprocessing. In particular, our framework is based on iterative arc swapping strategies and supports a number of use cases, from strengthening the resilience (e.g., in the presence of shared risk link groups) to improving the quality of the resulting routes (e.g., reducing route lengths and induced loads). Our simulations show that postprocessing is indeed beneficial in various scenarios, and can therefore enhance today's approaches.