BoCoVADI - Business Model oriented Cost and Value Engineering for the Digital Industry

The general goal is to systematically identify value drivers for digital systems and to be able to quantify thesevalue drivers in the context of a specific business model. Accordingly, the essential cost drivers and their associated cost have to be identified that are necessary to make the value proposition of a business model realizable. The relations between cost drivers and value drivers have to be made explicit in order to identify impact of cost changes on value drivers and vice versa. The cost and value engineering approach should be integrated with the TAICOS model in order to be able to refine cost and value engineering on selected tasks of a TAICOS model. Achieving the required quality level for a service based on a business model and well aligned with the value propositions is a challenge by itself. Furthermore, changes to the value proposition require continuous adaptation of quality assurance. In a model based world quality models help to make the abstract concept of quality tangible and facilitates automatic measurement and evaluation of arbitrary artefacts of the development process. Nevertheless, the larger these (quality) models get the more time consuming and difficult it is to setup and maintain them. The tool landscape changes, new and interesting tool players enter the market, new versions of tools are provided, etc. Currently maintenance of quality models is done manually, supported by some scripts. This is not feasible in a changing world, were value propositions have to be continuously tuned to meet the expectations of the customers. Machine Learning claims to provide mechanisms for language understanding, which could help in solving typical tasks in quality model maintenance. The project therfore also focuses on machine learning based maintenance of models with an emphasis on quality models, using established machine learning frameworks.