Business intelligence architecture models for measuring value for money in public expenditure systems

2026-03-13T10:54:40+00:00

Business Intelligence (BI) architecture models are increasingly critical for strengthening transparency, accountability, and performance measurement within public expenditure systems. This study develops a comprehensive BI architecture framework designed to measure and optimize Value for Money (VfM) across government budgeting, procurement, and service delivery processes. Persistent inefficiencies, fragmented data environments, limited performance visibility, and weak expenditure tracking mechanisms continue to undermine fiscal discipline in many public institutions. Addressing these challenges requires integrated analytics infrastructures capable of transforming raw financial and operational data into actionable intelligence. The proposed model adopts a layered BI architecture comprising data sourcing, data integration, storage, analytics, and visualization layers. It integrates financial management information systems (FMIS), procurement databases, audit records, and program performance datasets into a centralized data warehouse supported by real-time Extract, Transform, and Load (ETL) processes. Advanced analytics modules incorporate descriptive, diagnostic, predictive, and prescriptive techniques to evaluate economy, efficiency, and effectiveness dimensions of public spending. Key performance indicators include cost-efficiency ratios, budget variance analysis, procurement cycle times, service delivery outputs, and social impact metrics aligned with policy objectives. To enhance governance, the framework embeds data quality management, metadata standards, role-based access controls, and compliance monitoring mechanisms. Interactive dashboards and automated reporting tools provide policymakers, auditors, and oversight bodies with continuous performance visibility. Machine learning algorithms are further integrated to detect anomalies, identify fraud risks, and forecast expenditure trends under alternative policy scenarios. A multi-sector validation approach drawing on case analyses from health, education, and infrastructure expenditure systems demonstrates measurable improvements in decision accuracy, fiscal transparency, and resource allocation efficiency when BI-enabled models are implemented. Findings indicate that institutional leadership commitment, interoperable data standards, and digital capability development are key enablers of successful adoption. The study contributes theoretically by positioning BI architecture as a strategic governance capability rather than merely an IT function. Practically, it provides a scalable roadmap for governments seeking to institutionalize data-driven Value for Money assessment frameworks. By aligning analytics with fiscal responsibility and public accountability objectives, the model supports sustainable public finance management reforms in both developed and emerging economies.

Keywords: Business Intelligence, Value for Money, Public Expenditure, Fiscal Transparency, Data Governance, Analytics Architecture, Performance Measurement, Public Finance Management, Predictive Analytics, Accountability Systems.

Gulf Journal of Engineering & Technology

Business intelligence architecture models for measuring value for money in public expenditure systems