Data, information, knowledge and intelligence

Abstract

Purpose This paper is about data, information, knowledge and judgment; their definitions and their parallel cognitive dimensionalities; and it is about their implications in innovation. This paper aims to discuss and illustrate the implications of this cognitive framework on innovation science and on the ability to innovate. To that end, the authors use a progression of examples and cases to identify and discuss new challenges and predicaments in innovation. Design/methodology/approach The authors discuss how the development of Chemistry, as a science, inspires this work. But the authors have purposely eschewed examples from mathematics or the natural sciences. Instead, the authors study business examples because they are more readily understood. However, the implications they reveal, on innovation, are no less significant. The explosive volume, complexity and requirements – for data, information, knowledge and intelligence in business – are arguably more messy, demanding and difficult. They are sociotechnical problems of unprecedented scale and qualitative change. Findings The authors frame their conclusion as the mega-nano hypothesis, which asserts that problems, at this new scale and qualitative difference, cannot be solved with conventional thinking and tired mental models. They obstruct the ability to innovate and impede creative thinking about theory. Originality/value The mega-nano hypothesis is consistent with historical trajectories in scientific development. Namely, when there are mega or nano changes of scale and frame-breaking phenomena, a new science is required to address the new and unprecedented problems that emerge.