Abstract In the quest for market mechanisms that are easy to implement, yet close to optimal, few seem as viable as posted pricing. Despite the growing body of impressive results, the performance of most posted price mechanisms however, rely crucially on “price discrimination” in the presence of large supply or non-linear production costs. With this in mind, we study the problem of designing non-discriminatory pricing mechanisms for social welfare maximization in a Bayesian setting where the seller only has stochastic information regarding buyer valuations. Our main contribution is a framework for static item pricing in the face of production costs, i.e., the seller posts one price per good and buyers arrive sequentially and purchase utility-maximizing bundles. The framework yields constant factor approximations to the optimum welfare when buyer valuations are fractionally subadditive, and extends to settings where the seller is completely oblivious to buyer valuations. Our results indicate that even in markets with complex buyer valuations and nonlinear costs, it is possible to obtain good guarantees without price discrimination, i.e., charging buyers differently for the same good.