Advanced analytics for decision making in public management: a systematic review

Izquierdo-Mogollon S.M.; Maquen-Monja A.D.M.; Vásquez-Cornel J.A. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/leird2025.1.1.872

Resumen

The integration of advanced analytics into public sector decision-making is emerging as a key strategy for improving institutional performance and service delivery. The overall objective is to explore how advanced analytics techniques are used in decision-making processes within public management. To this end, 53 articles published in the last five years were reviewed, selected from the Scopus and Web of Science databases. The PICO strategy and PRISMA methodology were applied to organize the findings around three main points: the problems identified, the techniques used, and the benefits obtained. Among the main challenges identified are strategic decision-making without analytical support, operational inefficiency, limited crisis response capacity, limited focus on citizen equity, and weak data governance. The most used techniques were machine learning, advanced statistical analysis, and text mining. In terms of the most notable benefits, 64.15% of the studies highlight knowledge generation, followed by improved operational efficiency at 35.85%. However, aspects such as citizen participation and social impact remain largely unexplored. Finally, it is concluded that advanced analytics offers a significant opportunity to transform public management, although greater institutional maturity, strengthened technical capabilities, adequate data governance frameworks, and more robust empirical validations are needed. © LEIRD 2025.All rights reserved.

Instituciones: Universidad Tecnológica del Perú