Data-Driven Innovation: What Is It?
本文正式定义了数据驱动创新（DDI）这一新兴创新范式，区分了它与数据驱动优化、基于数据的创新及传统创新过程，并通过实例和理论框架阐明其如何应对不确定性、增强创造力，最后为创新者、企业、研发组织和政府提供了实施DDI的策略建议。
The future of innovation processes is anticipated to be more data-driven and empowered by the ubiquitous digitalization, increasing data accessibility and rapid advances in machine learning, artificial intelligence, and computing technologies. While the data-driven innovation (DDI) paradigm is emerging, it has yet been formally defined and theorized and often confused with several other data-related phenomena. This article defines and crystalizes “DDI” as a formal innovation process paradigm, dissects its value creation, and distinguishes it from data-driven optimization, data-based innovation, and the traditional innovation processes that purely rely on human intelligence. With real-world examples and theoretical framing, I elucidate what DDI entails and how it addresses uncertainty and enhance creativity in the innovation process and present a process-based taxonomy of different DDI approaches. On this basis, I recommend the strategies and actions for innovators, companies, R&D organizations, and governments to enact DDI.