Increasing concern about global climate change has led to a growing interest in energy usage and water consumption. It is well known that changes in consumption habits lead to more efficient use of energy and water sources. Nowadays, globalization, environmental concerns, and the shortage of resources have led to an increase of stakeholder pressure on companies to expand their focus to sustainability. Also, the high impact that the savings can have in the financial status of the company. It is encouraging the headboards to study and improve the ways water and energy are being used within the processes. Significant economic savings and benefits for the environment could be achieved with slight changes in the company. As an overview, this project starts with the extraction of data from a platform for energy management in an industrial company. Then, it goes through the understanding of the energy and water usage data set. Later, a methodology to handle and process the data will be set. It is intending to extract relevant information using clustering. The idea is to compare the usage profiles between different factories, using key performance indicators and reducing the initial data set. Once the benchmarking is performed, some critical parameters will be selected to support the decision-making process related to investments to reduce the energy usage and water consumption in a specific location. Finally, the case of study will be implemented with the measurements from Alfa Laval. We will study how, from daily measurements with a very low investment and using the proper algorithms and methodologies, the main behaviours and features in an industrial location can be extracted from the utilization data. These characteristics can be used to develop strategies or productions schemes based on the interests of the energy manager and the company.