Industry accounts for one-third of global final energy demand. Before the background of climate change and restricted resources, it is necessary to improve the energy efficiency of industrial processes. A key challenge for improving the energy efficiency is that industry is highly heterogeneous. The structure of the energy consumption in industrial enterprises depends on the character of the production process (e.g., primary energy resources, energy intensity of the products, production plan, and machinery). Energy efficiency targets include activities for single processes, as well as strategies for the complete enterprise. The energy analysis represents the first step of the optimization process. In many plants, the energy streams are only measured by a single meter at the source. The energy use of single processes is mostly unknown. The installation of additional measurement devices (e.g., flowmeters or wireless electric power meters) is one option to get more information about the energy distribution. Otherwise retrofitting of energy meters into running processes is difficult and in many cases impossible. Alternatively, we can use specific information coming from the automation system, which controls the production process. These data are collected by an energy information system (EMIS). The paper will describe a comprehensive methodology to realize an energy analysis. In industrial enterprises, crossover technologies play an important role for energy efficiency. They are characterized by a large number of applications independent of the production branch. They include motors and drives, pump systems, compressed air, lighting, process heat, and air conditioning systems. The crossover technologies are responsible for a large share of the industrial energy consumption. Especially electrical power is used by drives, pumps, compressors, and lightning. In many applications, there are common problems dealing with: low energy efficiency, oversized dimension of the system, lack of control, and maintenance deficits. In many cases, oversized and inefficient drives are still used in historically grown industrial enterprises with changing production programs. The exchange of long term running motors by new ones with high efficiency class saves much energy and costs. We will demonstrate the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control systems (PCS) can support EMS. They observe the performance of the production systems and organize the maintenance procedure. PCS contains the sensors and actuators that are required for the control of the processing plant. The sensors measure the process variables, i.e., temperature, pressure, mass flow, etc. The actuators receive signals from the controller level and perform a function, e.g., they start a pump or close a valve. PCS schedules and records the outcomes of maintenance testing, inspection, and repair. These may be supplemented by equipment monitoring tools, typically running in association with the plant process historian, which measure and evaluate the current equipment performance. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.