We define reconsideration, a non-prioritized belief change operation on a finite set of base beliefs. Reconsideration is a hindsight belief change repair that eliminates negative effects caused by the order of previously executed belief change operations. Beliefs that had previously been removed are returned to the base if there no longer are valid reasons for their removal. This might result in less preferred beliefs being removed, and additional beliefs being returned. The end product is an optimization of the belief base, converting the results of a series of revisions to the very base that would have resulted from a batch revision performed after all base beliefs were entered/added. Reconsideration can be done by examining the entire set of all base beliefs (both currently believed and retracted) --- or, if the believed base is consistent, by examining all retracted beliefs for possible return. This, however, is computationally expensive. We present a more efficient, TMS-friendly algorithm, dependency-directed reconsideration (DDR), which can produce the same results by examining only a dynamically determined subset of base beliefs that are actually affected by changes made since the last base optimization process. DDR is an efficient, anytime, belief base optimizing algorithm that eliminates operation order effects.