Data-driven innovation : Is big data the new source of business ideas?

Abstract

This research aimed to understand the potential of data-driven innovation (DDI) and answer the question whether big data is the new source of business ideas. Literaturereview uncovered that there is no universal definition of DDI although the main ideaof creating something new or a better version of something based on data is alwayspresent. I found a considerable number of empirical studies focusing on enabling factors(digital literacy, data-driven culture, IT & big data management capabilities, maturityof digital/data strategy) and DDI’s impact on a firm’s innovation and financialperformance. The highly interdisciplinarity and complex nature of the topic required a comprehensive conceptual phase in advance, gathering and tying up the “loose ends”of previous research. Following this iterative process, I finally formulated my researchquestions. Subsequently, I conducted five qualitative interviews with experts of different industries. The aim was to look at DDI from different angles and gain first-handpractical insights and best practice on how an organization needs to be set up, what (political, legal, technical) requirements are needed for DDI, and how data influence the innovation process. Based on the interviews, I drew the “Model of the DDI Ecosystem”,displaying relevant players/roles and influencing/enabling factors. I state that big data is a very valuable source of innovation but will not (entirely) replace other sources and conclude with “The 3 Faces of DDI” – (1) the usage of AI tools to increase efficiency in day-to-day business, substantially changing the way-of-working, (2) the usage of big data analytics, models, and machine learning for innovating and optimizing products, services, and processes in the existing business (as routine/targeted internal innovation or also data-driven optimization (DDO)) and (3) the usage of big datasets and analytics for the development of new products, services, or business models(as architectural or radical/disruptive external innovation or also data-based innovation(DBI)) that requires exchange of large amount of anonymized and aggregated dataacross company-, industry- and country-borders. Where as the first face of DDI is a“next level of software tools” and easy to implement, the second face requires more internal capabilities and competencies regarding data management, processing, and literacy. The third face is the most complex one, raising legal and ethical questions aswell as the issue of information/data security and entrepreneurial competitiveness. Finally,recommendations for further research were made for all the “3 Faces of DDI”.