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The goal of partial-order methods is to accelerate the exploration of concurrent systems by examining only a representative subset of all possible runs. The stateful approach builds a transition system with representative runs, while the stateless method simply enumerates them. The stateless approach may be preferable if the transition system is tree-like; otherwise, the stateful method is more effective. In the last decade, optimality has been a guiding principle for developing stateless partial-order reduction algorithms, and without doubt contributed to big progress in the field. In this paper we ask if we can get a similar principle for the stateful approach. We show that in stateful exploration, a polynomially close to optimal partial-order algorithm cannot exist unless P=NP. The result holds even for acyclic programs with just await instructions. This lower bound result justifies systematic study of heuristics for stateful partial-order reduction. We propose a notion of IFS oracle as a useful abstraction. The oracle can be used to get a very simple optimal stateless algorithm, which can then be adapted to a non-optimal stateful algorithm. While in general the oracle problem is NP-hard, we show a simple case where it can be solved in linear time.