Process model for data-driven business model generation

Digitalization is advancing fast and at the same time the volume of data is increasing. Examples from industry show that business models using big data can lead to competitive advantages. Currently the number of smart products is rising, which means more data will be available to engineering ompanies. The challenge is to extract additional profits and value from it. The literature review revealed that existing process models and methods for business model generation do not consider data in a distinct way. This paper synthesises existing work on business model generation and experience gained during a case study in an engineering student project to develop additional support for the generation of data-driven business models. The developed business model canvas helps to better outline the data requirements of business models. The developed process model describes the important phases for generating data-driven business models. The results of the case study indicate that the support helps to make the data perspective more visible and leads to new ideas. Furthermore, the support improves the coordination between product and business model development. The paper closes with a outlook.     «

Digitalization is advancing fast and at the same time the volume of data is increasing. Examples from industry show that business models using big data can lead to competitive advantages. Currently the number of smart products is rising, which means more data will be available to engineering ompanies. The challenge is to extract additional profits and value from it. The literature review revealed that existing process models and methods for business model generation do not consider data in a dis...     »