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 paper defines and crystalizes "data-driven innovation" as a formal innovation process paradigm, dissects its value creation, and distinguishes it from data-driven optimization (DDO), data-based innovation (DBI), 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 data-driven innovation approaches. On this basis, I recommend the strategies and actions for innovators, companies, R&D organizations, and governments to enact data-driven innovation.
翻译:预计创新进程的未来将更加以数据为驱动力,并被无处不在的数字化化、增加数据可获取性以及机械学习、人工智能和计算机技术的快速进步所赋予权力。数据驱动创新范式正在出现,但该范式尚未正式界定和理论化,而且往往与若干其他与数据相关的现象相混淆。本文将“数据驱动创新”定义为正式创新流程范式并加以化,将其价值创造与数据驱动优化、基于数据的创新(DDO)、基于数据的创新(DDI)以及完全依赖人类智慧的传统创新流程区分开来。在现实世界的实例和理论框架下,我阐述了DDI意味着什么,它如何解决创新过程中的不确定性,如何提高创新的创造力,并提出了不同数据驱动创新方法的基于过程的分类。在此基础上,我建议创新者、公司、研发组织和政府制定以数据驱动的创新战略和行动。