| Abstract |
Nowadays, innovation is an important competitive business advantage. Therefore, companies implement innovation processes or outsource them to external consulting companies. One example for such an innovation process is the methodology of design thinking, which enables the creation of innovative products or services. In Design Thinking an innovative product or service makes sense to people and for people, is likely to become a sustainable business model, and furthermore is functionally possible within the foreseeable future. Therefore, Design Thinking is considered as incubator for new innovative products and services. However, the transition from designing innovative products or services to implementing them is challenging since innovators and engineers are seldom the same people. This means a knowledge transfer between both groups is inevitable. As can be observed in practice, this knowledge transfer seldom goes smoothly since usually only the final innovative product or service is subject to the handover process. This is the case in spite of the fact that design decisions and the design path leading to this innovative outcome include important design rationales required by engineers. Thus, the design path and design decisions need to be recovered later on. We tackle this challenge with a manifold approach, which consists of (a) capturing design thinking artifacts, (b) inferring additional knowledge to recover the design path and design decisions, and (c) querying this knowledge. In this chapter we introduce our inference engine, which infers the design path and design decisions of Design Thinkers with the help of our Design Thinking inference rule set. |
