ADMINISTRATIVE SYSTEMS AS DATA INFRASTRUCTURES IN THE DIGITAL TRANSFORMATION OF THE STATE: A PROSPECTIVE ANALYSIS BASED ON A CASE STUDY
DOI:
https://doi.org/10.66104/7eepaq28Keywords:
State capacity; Digital transformation; People management; Data-driven governance; Public value.Abstract
This study examines how administrative systems focused on work management can operate as institutional infrastructures for the production of organizational data in the public sector. Drawing on a case study of the Integrated System for Attendance and Activity Management (SIGFA), currently under development at the State Secretariat for Planning of Piauí (SEPLAN/PI), Brazil, the article analyzes, from an analytical-prospective perspective, how the integration of people management, digital systems, and organizational data production may contribute to strengthening state capacity. Methodologically, the study adopts a qualitative approach, structured as a technical report based on a single case study, supported by organizational diagnosis, document analysis, and observation of institutional routines. The diagnostic findings highlight limitations of traditional time-control models, particularly regarding their limited capacity to generate structured information on institutional activities. Based on this evidence, the analysis suggests that integrated digital systems such as SIGFA may, under certain institutional conditions, enhance organizational monitoring capacity, improve internal coordination, and support data-driven decision-making processes. At the same time, the study indicates that such systems may contribute to reconfiguring traditional time-control practices, aligning them with result-oriented approaches and public value creation. Finally, it is argued that the replicability of such initiatives is conditional upon factors such as digital maturity, technological capacity, and the existence of data governance structures, positioning SIGFA as part of a broader—yet still evolving—movement toward data-driven public sector transformation.
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