Business Intelligence Applications in Water Utility Management: A Case Study Approach

Purpose: This study explores the application of Business Intelligence (BI) tools in the management of water utilities, focusing on how BI supports strategic decision-making, operational efficiency, and service improvement. Despite the abundance of operational data, many water utilities in developing countries struggle to fully integrate BI systems due to technical, cultural, and organizational barriers.Design/Methodology/Approach: A qualitative case study methodology was used, involving semi-structured interviews with management and technical staff, document analysis, and limited observation. Purposeful sampling identified key informants, and thematic analysis was applied to the collected data to extract recurring themes related to BI applications and outcomes.Findings: The findings reveal that BI tools—such as dashboards, data warehousing, and reporting systems—are being increasingly integrated into utility management. These tools have enabled real-time monitoring, improved customer insights, and data-informed financial planning. However, challenges remain in the form of technical integration barriers, staff capacity gaps, and cultural resistance to data-driven practices. Despite these challenges, the organization demonstrates a clear commitment to BI as a driver of performance and innovation.Originality/Value: This research contributes to the limited body of knowledge on BI in public utilities, particularly in developing country contexts. The study offers practical insights into how water utilities can adopt BI effectively and proposes recommendations for improving BI readiness, organizational alignment, and data governance.

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Publication Details

Journal
Manar Elsharq Journal for Management and Commerce Studies
Published
2025-08-22
DOI
https://doi.org/10.56961/mejmcs.v3i3.1076
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Business Intelligence Applications in Water Utility Management: A Case Study Approach

Mohammad Qwaider Alamro
Manar Elsharq Journal for Management and Commerce Studies
Big Data and Business Intelligence
article

Business Intelligence Applications in Water Utility Management: A Case Study Approach

Mohammad Qwaider Alamro
article en

Abstract

Purpose: This study explores the application of Business Intelligence (BI) tools in the management of water utilities, focusing on how BI supports strategic decision-making, operational efficiency, and service improvement. Despite the abundance of operational data, many water utilities in developing countries struggle to fully integrate BI systems due to technical, cultural, and organizational barriers.Design/Methodology/Approach: A qualitative case study methodology was used, involving semi-structured interviews with management and technical staff, document analysis, and limited observation. Purposeful sampling identified key informants, and thematic analysis was applied to the collected data to extract recurring themes related to BI applications and outcomes.Findings: The findings reveal that BI tools—such as dashboards, data warehousing, and reporting systems—are being increasingly integrated into utility management. These tools have enabled real-time monitoring, improved customer insights, and data-informed financial planning. However, challenges remain in the form of technical integration barriers, staff capacity gaps, and cultural resistance to data-driven practices. Despite these challenges, the organization demonstrates a clear commitment to BI as a driver of performance and innovation.Originality/Value: This research contributes to the limited body of knowledge on BI in public utilities, particularly in developing country contexts. The study offers practical insights into how water utilities can adopt BI effectively and proposes recommendations for improving BI readiness, organizational alignment, and data governance.

Manar Elsharq Journal for Management and Commerce StudiesVol. 3(3)
University of Kara (TG)
Openalex Percentile: Top 59%
Big Data and Business Intelligence
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