# Digital Twin-Enabled Decision Support Services in Industrial Ecosystems
## 4 Results
### Integrating the Domains to a Hierarchical Concept  
In a service ecosystem comprising several enterprises and a multitude of actors each having jobs to perform and decisions to be taken, usually a multitude of digital twins is required to provide decision support services to these actors. This decision making is structured in a hierarchical way following the structure of the ecosystem. The overall performance metrics can be divided into submetrics for the different hierarchical levels, e.g., a company sets a goal for the annual production output. This goal can be divided into required outputs and delivery times for the different actors in the ecosystem, which may be business units of the same company or from different companies in the ecosystem. This structure is indicated in Figure 4 by the pyramid and the KPI (key performance indicator) tree. The KPI tree includes the main KPIs, as well as the derived basic KPIs and key performance parameters (KPP) on the shop floor level as suggested by [34]. This results in several specific business challenges for different actors on different hierarchy levels, each with specific decision support needs. Depending on the information and data available, a digital twin lends itself for supporting these decisions. This will result in a digital twin landscape over the entire ecosystem with each digital twin serving a specific process owner. The individual digital twin is represented by the vertical boxes labeled \"DT sequence\" in Figure 4. The digital twin is thereby not limited to the hierarchy level of the process owner. It might reach over several underlying hierarchy levels depending on its scope, as well as on the system topology. A systematic development procedure consisting of six steps for the DT sequence is discussed in [35]. While isolated digital twins might have a significant value-add to the process owners, fostering the full potential requires connecting and integrating all the digital twins. In other words: an isolated twin represents untapped potential. Thus, the digital twins need to be coordinated and integrated across the entire service ecosystem. Doing so enables the prediction of the effects of decisions made on one specific hierarchy level on the performance of the processes of other hierarchy levels or ecosystem actors. This enables decisions to be made not only focusing on the local KPIs but on the overall performance of the ecosystem. Moreover, the coordinated design of the digital twins across the ecosystem draws attention to potential further digital twins that can generate additional benefits and thus close gaps in the overall hierarchical system of digital twins. The use of strategy deployment to cascade and translate performance metrics and KPIs is described by [36]. The approach, to be practical, requires the translation of performance metrics into metrics that are relevant for the actors at their particular level in the organization. The translation builds relevance to the actors, allowing them to take better actions based on decision making that includes an understanding of the consequences. Ref. [37] describes how strategy deployment is part of a continuous learning process and  
Figure 4: Hierarchical interplay between the different modeling domains. can change behaviors between different actors. This is important, as technical decisions in the organizations can impact the business outcomes. Negotiations are required to allow discussions between different levels within the business (with different perspectives and business languages), and the translations of metrics can support the decision making that subsequently takes place. This is particularly important as we move from one business area to another [38]. The integration of such strategy deployment within the context of a digital twin is described by [39]. The connection and integration of different digital twins requires the implementation of a new role, which we call the digital twin champion (DTC). The DTC manages and synchronizes the implementation and integration of different digital twins.