## 2 Literature Review of the Problem
Along with it, there is also the possibility of visibility of real-time data. Thanks to the visibility of data, production companies can track their production activities in real time. They can monitor production lines, inventory levels and other key performance indicators (KPIs), such as the total equipment efficiency (OEE) to identify problems as they appear and improve your actions [39]. This allows you to immediately undertake repair actions, minimizing unplanned downtime and limiting losses. By analyzing data from all devices and combining this information in one place, as another researcher points out the possibility of easy identification, from machines or production lines requires quick intervention and more detailed analysis [40]. Thanks to this, you can react quickly to avoid unplanned downtime [41]. The data placed in the appropriate pads allow us to assess whether potential changes and innovations (aimed at eliminating problems and improving production efficiency) meet their assumptions. In addition, thanks to the continuous measurement of efficiency, it can be quickly assessed whether the correct direction of changes has been chosen whether the pace of these changes is acceptable and, most importantly, whether the costs incurred at these innovations will pay back at the time designated during the time [42]. The production line with the lowest OEE indicator is not always the factor that inhibits the performance of production processes. Looking at the problem more broadly, having not only production data at your disposal but also orders and implementation times--you can assess where there are real gaps in the production capabilities of machines. The OEE indicator is a great tool to determine where you should potentially invest time and money [43]. Thanks to access to data, manufacturers can track reserve levels and use patterns. This allows you to optimize inventory, ensuring that they have enough materials and supplies on hand--but without excessive stocks. By reducing excessive stocks, manufacturers can release space and capital, obtaining better financial results. Real-time visibility allows manufacturers to monitor the quality of their products throughout the entire production process. They can track and analyze data from sensors and other sources to identify early potential quality problems [44]. This enables recovery actions before producing defective goods. This reduces the amount of waste and increases the satisfaction of end customers. In addition, it affects sustainable development by reducing the carbon trace and of course reduction of operating costs [45]. The analysis of scientific literature on the effectiveness of production processes indicates numerous studies on general concepts of optimization, such as Lean Manufacturing, Six Sigma or Total Productive Maintenance. These methods are widely used in the automotive industry, but theoretical research often focuses on general principles or large production systems, ignoring detailed analyses of local optimization activities, such as workshops conducted at the level of a specific process or workplace. The research gap is focused on the lack of detailed analysis of the impact of optimization workshops as well as the implementation of technology and updating procedures on the effectiveness of production processes. The tests performed by analyzing empirical data before and after the workshop fill this gap, providing current information about the effectiveness of optimization activities in automotive enterprises. Constituting an important contribution, both practical and theoretical, to the research topic mentioned by the authors.