In today’s rapidly changing business environment, the case for accelerated innovation processes has become increasingly compelling at both a theoretical and practical level. Thus, the purpose of this paper is to propose a conceptual framework for accelerated innovation in a data-driven market environment.
This research is based on a two-step approach. First, a set of propositions concerning the best approaches to accelerated innovation are put forward. Then it offers qualitative evidence from five case studies involving world-leading firms, and explains how innovation can be accelerated in different kinds of data-driven environments.
The key sets of factors for accelerated innovation are: collateral structure; customer involvement; and ecosystem of innovation. The proposed framework enables firms to find ways to innovate – specifically, to make product innovation faster and less costly.
The findings from this research focus on high-tech industries in China. Using several specific innovation projects to represent accelerated innovation could raise the problem of the reliability and validity of the research findings. Additional research will probably be required to adapt the proposed framework to accommodate the cultural nuances of other countries and business environments.
The study is intended as a framework for managers to apply their resources to conduct product innovation in a fast and effective way. It developed six propositions about how, specifically, data analytics and ICTs can contribute to accelerated innovation.
The research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation framework is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.
