The design of new and better heterogeneous catalysts needed to accommodate the growing demand for energy from renewable sources is an important challenge for coming generations. Most surface catalyzed processes involve a large number of complex reaction networks and the energetics ultimately defines the turn-over-frequency and the selectivity of the process. In order not to get lost in the large quantities of data, simplification schemes that still contain the key elements of the reaction are required. Adsorption and transition state scaling relations constitutes such a scheme that not only maps the reaction relevant information in terms of few parameters but also provides an efficient way of screening for new materials in a continuous multi-dimensional energy space. As with all relations they impose certain restrictions on what can be achieved and in this paper, I show why these limitations exist and how we can change the behavior through an energy-resolved approach that still maintains the screening capabilities needed in computational catalysis.