Implementation and Validation of a Business Intelligence Dashboard for Business Process Monitoring
Abstract
Research Context: Business Process Management (BPM) is fundamental for competitive advantage and governance, especially in the public sector, where continuous monitoring supports strategic decision-making and performance improvement. Business Intelligence (BI) tools play a central role by linking process execution with managerial analysis. Scientific and/or Practical Problem: The process dashboard of the Court of Auditors of Pernambuco (TCE-PE) faced performance limitations and data inconsistencies, resulting from dependence on multiple SQL Server views. These views were shared across departments, which applied different data treatments, compromising information consistency and accurate visualization of key performance indicators. Proposed Solution and/or Analysis: This study proposes and validates the implementation of a new Process Dashboard using Qlik Sense, based on an architectural intervention that eliminates dependency on multiple views by centralizing transformation logic within the BI tool itself. Related IS Theory: The new tool was evaluated according to the DeLone and McLean Information Systems Success Model, covering dimensions of Information Quality, System Quality, Service Quality, Use/Intention to Use, User Satisfaction, and Net Impacts. Research Method: The research followed the Design Science Research Methodology (DSRM), structured into six stages (Problem Identification, Objective Definition, Design and Development, Demonstration, Evaluation, and Communication), conducted incrementally with institutional stakeholders. Summary of Results: The new dashboard eliminated reliance on external views, resulting in greater data consistency, easier maintenance, and improved process visualization reliability. The empirical evaluation with key users revealed a positive perception across all dimensions, with the highest scores in Net Benefits and Service Quality. Contributions and Impact to IS area: This study presents a validated model for restructuring data flows in BI environments within the public sector, addressing root causes of data inconsistencies and information quality issues. By centralizing data transformation, it strengthens reliability, transparency, and monitoring capacity, offering practical and theoretical contributions to the Information Systems field.
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