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

  • Juan Luis Peñaloza Figueroa Department of Statistics and Operations Research IIComplutense University of Madrid
  • Carmen Vargas Pérez

Abstract

.The dominant perspective in Business Intelligence (BI) projects and applications has been the technological conception, usually focused on the technical-instrumental nature of computing. This conception has avoided the change in the paradigm from a business model based on the use of tangible resources in favour of one based on the exploitation of intangible resources (data, interaction, networks, etc.). This would explain why applied BI projects, remain anchored in the old organization and operational patterns of traditional businesses in most companies. The technological perception of BI gives continuity to the stovepipe activity of companies, both in their management and in their organizational structures, where the impact of interaction as a generator of business opportunities is very limited, and often non-existent; and the effect of large volumes of data as a value generator is reduced to an operational and technical problem. Hence, the importance of considering BI as a new business philosophy that entails new forms of business organization and a new way of management based on the interaction and analysis of large volumes of internally generated data. Our interest is not only to emphasize the nature of the new business philosophy in the application of BI, but to carry out a discussion about the organizational and operational structure of businesses -according to a conception based on interaction and data as generators of business value-, and about actionable intelligence.
Published
Jun 10, 2017
How to Cite
FIGUEROA, Juan Luis Peñaloza; PÉREZ, Carmen Vargas. Business Strategies Based on Large Sets of Data and Interaction: Business Intelligence. European Journal of Economics and Business Studies, [S.l.], v. 9, n. 1, p. 156-167, june 2017. ISSN 2411-9571. Available at: <http://journals.euser.org/index.php/ejes/article/view/2564>. Date accessed: 23 nov. 2017. doi: http://dx.doi.org/10.26417/ejes.v9i1.p156-167.