## 4 Discussion
An analysis of the result and methodology, replicable in similar use cases, reveals clearly some key steps for the design of the DT for the ETO process. By tracking the implementation and evaluation of features based on user stories, this study contributes to the body of knowledge on the effectiveness of UCD methodologies in industrial settings, supporting the adoption of 14.0 and 15.0 based on a bottom-up approach. The development of user stories through a collaborative process with diverse stakeholders proved crucial for aligning the DT with the specific needs of the workforce in the ETO environment. This user-centric approach, advocated for in DT research, not only fosters acceptance of new technologies in the early stage, as demonstrated by the interactive process, but also ensures that the system delivers tangible benefits to those who interact with it daily. This is also particularly relevant for the collaborative approach to define with the users measurable and verifiable performance metrics. The KPIs identified in the user stories, such as truck turnaround time, picking time, and NCRs due to loss, helps users to understand what they would like to achieve while providing a basis for quantitative assessment of the digital twin's impact on warehouse performance and the implementation of specific business intelligence activities with the data interoperated within the DT. Another result is that analyzing the user stories by user group can reveal patterns in requirements and priorities, highlighting the unique needs of different stakeholders. It appears that for all the users groups the KPIs are more oriented toward optimization and efficiency (19 of 26 user stories, 73%) to avoid time-consuming activities and inefficiency, while safety KPIs for prevention measures and control have a minor relevance for the current organization (7 of 26 user stories, 27%). A further interesting analysis, not conducted within the scope of this research, is related to the prioritization of user requirements and, consequently, technical ones. The user stories can be used to prioritize the development of specific technical features within the digital twin based on their potential impact on user satisfaction and overall warehouse performance. For this activity, the involvement of middle and top management is also a key step to have an alignment between the DT and business strategy based on performance productivity, certification acquisition, or other strategic parameters. Indeed, this KPI monitoring in the DT also helps it to be aligned with company activities across the project delivery process, such as quality control--the goal is to ensure that all prefabricated building envelopes meet the highest quality standard--and the company project management for the production activities--the goal is to deliver prefabricated facades on time, and in line with projects milestones. Additionally, the adoption of KPIs has emerged to be aligned with opportunities for certification improvement to guarantee quality control and track improvement year by year in the already-achieved certifications such as ISO 9001 [1], to assess and improve the quality management system, ISO 14001 [2], to assess and improve the environmental management system, and ISO 45001 [3], to assess and improve the safety management system. The processes and user identification presented in the results will help also to address further platform implementation at different stages, defining user interfaces (UId) and user experience (UX) related to specific tasks and requirements defined by the users. The implementation of this UI is not in the scope of the present paper, and it will be analyzed during platform implementation. The integration of BIM, IoT, and AI within the DT architecture confirms the novelty of the approach to warehouse management; to support the integration of BIM and IoT in manufacturing with the incorporation of AI algorithms for real-time analysis and decision-making is a distinct advancement.