## 6 Conclusions  
Despite increasing as the focus of discussions since 2019, the interaction of lean management and I4.0 is not yet fully understood. We have taken two main perspectives from the existing literature: The first sees lean management as the foundation for I4.0, as processes must first be optimized and standardized before new technologies can be introduced. The second recognizes the limitations of lean management and sees I4.0 as an opportunity to overcome them. Based on previous research, the integration of lean management and I4.0 promises more efficient communication, real-time decision-making through improved data collection, transparency, and analysis, and increased flexibility and productivity by minimizing waste in processes. Despite these already-known potential benefits, there is a need for empirical research to observe these in practice and better understand how lean management and I4.0 are and can be effectively combined and \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline  & **Continuous Improvement Without Digitalization** & **Continuous Improvement Reinforced by Digitalization** \\ \hline Flexibility & manual, tedious, time-consuming data gathering/access & automated, fast, transparent, reproducible gathering of/access to data \\ \hline Transparency & unclear by who, how, when, and where data were collected process “black-boxes” unclear where process improvements are hidden & at any time, it is known where the data come from and by who, when, and how it was collected; improved process understanding better visibility of the potential for improvement. \\ \hline Reliability & error-prone due to human involvement, possibility of dressing up numbers, differences in OEE calculation & reproducible, low risk of falsification, automatic and consistent collection and calculation \\ \hline Decision-making & half-true and inconsistent OEE, instinct, gut feeling, interpretation & reflects facts, is verifiable, uniform decision base \\ \hline Acceptance of change & susceptibility to errors known, different data and calculation methods produce different results, poor visualization & transparency in data collection, demonstrable, verifiable, visualization of decision bases \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Continuous (process) improvement through digitalization. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline \multirow{3}{*}{Plan} & \multicolumn{1}{c}{**Observed Improvement Factors**} \\ \cline{2-3}  & - & Transparency for processes and improvement potential identification \\  & - & Improved planning/optimization possibilities through better process understanding \\  & - & Flexibility in data acquisition, access, and application \\  & - & Acceptance of change through involvement and identification of potential \\ \hline Do & - & Improved communication and more efficient exchange of information/data of process through data collection \\  & - & Improved transparency in process flows and change events through data collection \\ \hline Check & - & Sensor-based data increases reliability of data/results with less likelihood of error sources and corruption \\  & - & Data-based decision-making increases the improvement potential \\ \hline Act & - & Improved decision-making processes through the reduction in errors in information used as a basis for decisions \\  & - & Acceptance through visualization of results and trustworthiness of data \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Summary—observed and generalized improvement factors provided by digitalization for lean management. implemented. With our studied use cases, we have shown that companies must first reach a certain level of lean maturity before they can implement digitalization, confirming perspective one. Lean and standardized processes take the complexity out of digitalization, enable the easier implementation of technologies, and prevent waste from being digitalized instead of eliminated.