# Value Creation with Digital Twins: Application-Oriented Conceptual Framework and Case Study
## 4 Application-Oriented Digital Twin Framework
### From Data to Value
Unstructured and semi-structured data require preparation efforts according to the analysis and processing methods requirements before they can be interpreted. Therefore, semi-structured data is not further distinguished from unstructured data in the model. Structured data, on the other hand, is either the result of proper data processing or originates from external sources providing data-as-a-service. These data are thus characterized by a high degree of organization, clarity, and consistency [20], hence most data in internal information systems can be considered structured [77], but also many external data providers deliver structured data, for example, market information, such as exchange rates or sales numbers, search engine advertisement data or weather data. Traditional design methods, data life cycle management tools, and databases are developed to interpret structured information. Therefore, they are not suitable for dealing with the unstructured information generated without predefined models or formats [20]. Different authors embrace how to improve the data life cycle management in the DT context to achieve interpreted information that can be potentially used for automated interpretation in terms of decision--and sense-making (e.g., [15; 64; 72]). The more data is automatically interpreted by the DT, the higher the smartness maturity and the more solutions are implemented without involving users. The \"user\" in our framework can be either a human actor or another DT. DTs of systems may access the DTs of subordinate units or components and simultaneously may have a common objective and be aggregated to a composite system of systems DT (e.g., [17; 22; 23]). Therefore, users  
Figure 7: From data to services to value creation with digital twins. in such ecosystems might often be other SCPs, systems, system of systems, or their DTs, interpreting structured data and requesting data-driven services. **From services to value--**The research on how the various components of DTs are encapsulated in services and used is not well-established [17]. However, the integration between DTs and services is promising, as new services can be enabled, and existing services can be enhanced by the new data supplied by DTs [21]. The common aim of the DT is to support the realistic model of system behavior that can support often already established services such as performance prediction and optimization [16]. However, concerning the concept of everything-as-a-service, services could fully release the potential of DTs [17], as the DT lends itself to contribute to the value proposition by supporting all of the actors around the product-service-system, in particular by relieving the pains and increasing the gains of the actors in new ways [45]. The attributes of a DT-based service can be defined in line with the widely recognized and used the concept of overall equipment effectiveness (OEE) that evolved into Total Productive Manufacturing. According to [PERSON] [78], OEE measurement is an effective way of analyzing the efficiency of a single machine or an integrated manufacturing system. OEE is a function of availability, performance, and quality rate calculated as the product of its three contributing factors [79]. Especially in smart manufacturing and industrial IoT, this encapsulation of DT-based services seems promising, as the OEE concept is widespread and clearly defined by several norms (e.g., VDMA). However, to achieve a holistic perspective on DT-based services, the definition of OEE is too narrow. Still, it can be supplemented with an overall service effectiveness (OSE) concept applicable to describe data-based service [80]. [PERSON] [80] elaborates the main contributing factors for services: Availability or time of the service is represented by the time needed between the occurrence at the customer triggering the need and the delivery of the service satisfying the need. The performance or cost contribution factor describes the relationship between input and output from the view of the customer.