Compendium law in iterative information management: A comprehensive model perspective

Abstract

The existing limitations of the fundamental laws necessary for constructing a comprehensive and widely accepted theoretical framework have significantly hindered the progress of Information Management. This lack has resulted in a predominant reliance on indirect strategies to address information management challenges, often leading to complex, inefficient, and somewhat stochastic analyses and evaluations. For instance, the failure rate of digital transformation in global enterprises is as high as 80 %, and that of data-driven organizational change reaches 85 %, highlighting the urgency and difficulty of resolving these challenges. Through an in-depth analysis of the spiral model and derivation of the Shannon-Weaver model, we unearthed the objective and universal Compendium Law of iterative information management. Building on this law, we propose the application of information system modeling and Hamiltonian graph theory to develop a comprehensive analytical model for iterative information management. This model provides a theoretical approach for the scientific analysis and optimal design of iterative information management, enabling efficient comparative analysis and knowledge transfer among various iterative information management systems. This study contributes to the foundational understanding of Information Management as an independent discipline capable of addressing cross-disciplinary challenges related to information resources, including those found in artificial intelligence, blockchains, quantum communication, the Internet of Things, and digitization.