Reconstituting knowledge management

Abstract

Purpose The purpose of the paper is to improve traditional knowledge management models in light of complexity theory, emphasizing the importance of moving away from hierarchical relationships among data, information, knowledge, and wisdom. Design/methodology/approach Traditional definitions and models are critically reviewed and their weaknesses highlighted. A transformational perspective of the traditional hierarchies is proposed to highlight the need to develop better perspectives. The paper demonstrates the holistic nature of data, information, knowledge, and wisdom, and how they are all based on an interpretation of existence. Findings Existing models are logically extended, by adopting a complexity‐based perspective, to propose a new model – the E2E model – which highlights the non‐linear relationships among existence, data, information, knowledge, wisdom, and enlightenment, as well as the nature of understanding as the process that defines the differences among these constructs. The meaning of metas (such as meta‐data, meta‐information, and meta‐knowledge) is discussed, and a reconstitution of knowledge management is proposed. Practical implications The importance of understanding as a concept to create useful metaphors for knowledge management practitioners is emphasized, and the crucial importance of the metas for knowledge management is shown. Originality/value A new model of the cognitive system of knowledge is proposed, based on application of complexity theory to knowledge management. Understanding is identified as the basis of the conversion process among an extended range of knowledge constructs, and the scope of knowledge management is redefined.

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