Warehousing plays a crucial role in global supply chains, significantly impacting energy consumption and emissions. Various green warehousing measures have been identified to help reduce the environmental impact of warehousing processes. However, the economic and environmental benefits of these measures remain unclear, and companies are struggling to find the right balance between achieving economic savings and minimizing environmental impact. For this reason, this study developed a matrix-based framework to help decision-makers rank sustainability interventions based on their environmental and economic impacts. The framework is applied to two industrial business cases, where the as is scenario is first assessed with the support of simulation, providing a detailed energy breakdown that the analysis of areas for improvement. To be scenarios for energy efficiency improvements are identified and applied in the matrix-based framework that display results in terms of both environmental and economic dimensions. This approach underscores the importance of data-driven decision-making in enhancing sustainability and operational efficiency. The findings offer actionable decarbonization strategies and identify best practices for green warehousing in the logistics sector. Additionally, the framework offers an easy-to-use tool for practitioners to prioritize and scale green interventions across their warehouse portfolio.