Integrating business intelligence into executive information systems for advanced decision support

Abstract

Purpose: to examine the integration of Business Intelligence (BI) into Executive Information Systems (EIS) to improve the quality of executive decision-making and identify key factors affecting its effectiveness.

Method: this study employs a qualitative descriptive approach. Data were collected through in-depth interviews, observations, and documentation involving executives, IT managers, and data analysts at an organization implementing BI and EIS. Data were analyzed using an interactive model consisting of data reduction, data display, and conclusion drawing, with triangulation used to ensure data validity.

Findings: the integration of BI and EIS is not yet optimal. EIS is still primarily used as a reporting tool with limited analytical capabilities, while BI operates separately from executive decision-making processes. Key challenges include data quality issues, technical integration constraints, limited user competence, inadequate visualization, and an organizational culture that is not fully data-driven.

Implications: the need to improve system integration, data quality, user literacy, and visualization, as well as to promote a data-driven culture to enhance decision-making effectiveness.

Originality: lies in proposing a holistic view of BI–EIS integration by addressing not only technical aspects, but also data quality, user competence, and organizational culture in executive decision support.