How to Support Real-time Quantitative Big Data by More Future Orientated Qualitative Data for Understanding Everyday Innovative Businesses?

The primary goal of this chapter is to support the decision-making process in innovation strategy. It proposes a quantitative model for decision-making in the area of innovation strategy keeping in mind sustainable competitive advantage concept. Innovation is a data-intensive process and companies that take it serious produce huge amounts of data from the initial idea development to further analyzing it during the innovation process. Simultaneously, data, in general, and big data particularly are great sources of innovation. When the size of data exceeds a certain limit, the innovation process starts to store, analyze, and find practical implementation to use it in a way that could bring competitive advantage to the company. This chapter considers four innovation strategies: inside-out, outside-in, coupled innovation, and closed innovation strategy in which the first three strategies belong to open innovation category. Using analytical hierarchy process and manufacturing strategy index concepts, this chapter proposes the innovation strategy index and applies it in two case companies operating in biotechnology and in vitro diagnostics industries. The results show that ISI correlated with the past and future innovation strategy status, and the model helps companies to maintain their competitive advantage in the global turbulent business environment.©2020 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Management in the Era of Big Data: Issues and Challenges on 15 June 2020, available online: https://www.taylorfrancis.com/chapters/edit/10.1201/9781003057291-17/fi=vertaisarvioitu|en=peerReviewed