Looking back at the past decades, one thing becomes clear: data has had a huge impact on organizations at all levels. Whether it's statistical analyses, big data or artificial intelligence, data will shape business performance in the years to come. One the one hand, even simple analyses with limited datasets can be highly effective in helping companies make better decisions, manage and optimize business processes, gain a deeper understanding of customers, and improve products and services. On the other hand, artificial intelligence holds the promise to completely transform business models and therefore has gained the most attention. The use of data to gather information and support decision-making has become a central pillar in many companies. Data analytics provides the opportunity to extract valuable insights from data, optimize business processes, and make informed decisions. But what is the current state of Manufacturing Data Analytics in the DACH region? In order to clarify this question, we conducted an empirical study that looked at data analytics in manufacturing companies, examining four key aspects. First, we investigated how manufacturing companies develop strategies and structures for integrating data analytics into their operations. Second, we examined the characteristics of manufacturing data to understand how data can be used effectively. The dimensions analysed included data collection, storage, processing, and exploitation. Third, we examined the relationship between lean management, digitalization, and data analytics. We analysed how these strategies work synergistically to streamline and optimize manufacturing processes. Finally, we analysed the impact of data analytics on business performance. Through a detailed assessment, we derived insights into the measurable impact on a company's overall performance, highlighting how data-driven insights can significantly increase business efficiency. The results of our study highlight existing barriers and areas where further research is needed. We see this effort as a further step towards data-driven manufacturing, enabling manufacturing companies to strengthen their competitive position through higher quality and productivity.