Uncertainties with respect to the chemical composition of scrap limit its suitability as an input to recycling. This study offers an alternative approach in dealing with this concern and explores the hypothetical case where this uncertainty is nonexistent. The effect of fully knowing the scrap composition is simulated using an optimization software adopted to scrap-based, stainless-steel production. Through the systematic implementation of this information-driven model in the studied cases, the results suggest that with access to perfect information, recycling incentives can be realized. Essentially, the steel scraps’ consumption increased since it was possible to select and combine scrap quantities with varying composition profiles to achieve the targeted product compositions. This also meant that elements already in the scrap were allocated in a manner that was less dependent on pure alloy additions. Being able to demonstrate the value of information on scrap composition could rationalize upgrades on current scrap management systems.