The commercial real estate sector contributes a sizable share to greenhouse gas emissions from the built environment due to its structural characteristics. The existence of an energy efficiency gap (EEG) between potential cost-effective measures and the actions being undertaken by the property industry has been subject to debate in the extant literature. Proponents of the EEG point to principal-agent problems, regulatory and technological risk and uncertainty over future energy prices as important drivers. Despite government-led efforts to decarbonise the sector through incentivisation of energy efficiency retrofits, evidence has emerged that a simple “fix and forget” approach will not suffice for large air-conditioned properties with complex systems and numerous stakeholders involved. Specifically, several studies have found that there is relatively little correlation between the proven energy efficiency of a building in operation and its energy performance certificate. This study tests if US office buildings with proactive energy management practices 1) consume less energy and, as a result, 2) command higher rental premia. Hence, the suggested study sets out to first survey and classify the efficiency of operational practices of a building, which past studies have not taken into account. These components can be found in the existing LEED dataset and include the frequency of commissioning and implementation of capital measures to upgrade energy efficiency equipment, the presence of building automation systems and advanced metering infrastructure. These measures are then analysed with a difference-in-difference approach and more advanced techniques. The results of this analysis will be valuable to policymakers, particularly in the UK and other European countries that are about to embark on an ambitious net zero carbon policy for commercial and domestic buildings. Information on achieved rents, as available from the CompStak database, is regressed on the constructed operational efficiency variable while controlling for a number of confounding variables. The insights shed light onto the potential financial returns to these measures in the office sector.