Business Strategies Based on Large Sets of Data and Interaction: Business Intelligence

Abstract

The dominant perspective in Business Intelligence (BI) projects has historically been constrained by a purely technological conception that focuses heavily on the technical-instrumental nature of computing. This narrow view has unfortunately hindered a critical paradigm shift away from traditional business models reliant on tangible resources toward modern frameworks that exploit intangible assets like data, interactions, and decentralized networks. Consequently, many applied BI projects remain stubbornly anchored in outdated operational patterns, continuing the stovepipe, siloed activities of legacy corporate structures where the impact of digital interaction as a generator of new business opportunities is severely limited. Under this tech-centric view, the transformative value of big data is often reduced to a minor operational and technical problem rather than a strategic asset. To overcome these limitations, this paper argues for re-conceptualizing BI as a comprehensive business philosophy that demands new forms of organizational architecture and a modern management style centered on data analysis and ecosystem interaction. Our objective is not only to emphasize the cultural and philosophical shift necessary for successful BI application, but to actively drive a rigorous discussion regarding how corporate structures must adapt when data and interaction are viewed as the primary drivers of business value. Ultimately, this research lays the groundwork for generating actionable intelligence, providing a conceptual blueprint for organizations aiming to break down traditional structural silos, capitalize on massive internal data volumes, and foster corporate agility within a volatile, hyper-connected global marketplace.