Data to Decision: Knowledge-Intensive Services for Asset Owners

In this paper, we present a data to decision framework which describes the content and role of data as the basis of knowledge-intensive services. The framework also depicts the process of systematically increasing the value of the data by refining it with population and/or ecosystem-related knowledge. The aim of the framework is to structure what kind of knowledge-intensive services the asset owner might need, when they might need them, and how capable the manufacturer is currently or wants to be in the future of providing these services. In many cases, the asset manufacturer provides data services, which are basically technical solutions for data collection, and it is the asset owner's responsibility to refine the collected data to support decision-making. Asset owners typically have a view of only one or a few similar systems, while the system manufacturers may have experiences of several systems and can form a deeper understanding of the system behaviour. Thus, the manufacturers can provide more intelligent knowledge-based services if they can collect and analyse data from the operation phase of the asset life cycle and combine it with business knowledge. As a result, knowledge-intensive services require good analysis skills but also a good understanding of the customer's business environment. By positioning their own skills and capabilities according to the data with a business knowledge model, a manufacturer can assess opportunities to provide knowledge-intensive services.