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

Abstract

The integration of advanced analytics in public sector decision making is emerging as a key strategy to improve institutional performance and service delivery. The general objective is to explore how advanced analytical techniques are used in decision-making processes within public management. To this end, 53 articles published in the last five years, selected from databases such as Scopus and Web of Science, were reviewed. The PICO strategy and PRISMA methodology were applied to organize the findings around three main points: the problems identified, the techniques employed and the benefits obtained. Among the main challenges identified were: strategic decision making without analytical support, operational inefficiency, limited crisis response capacity, limited focus on citizen equity and weak data governance. The most commonly used techniques were machine learning, advanced statistical analysis and text mining. The integration of advanced analytics in public sector decision making is emerging as a key strategy to improve institutional performance and service delivery. The general objective is to explore how advanced analytical techniques are used in decision-making processes within public management. To this end, 53 articles published in the last five years, selected from databases such as Scopus and Web of Science, were reviewed. The PICO strategy and PRISMA methodology were applied to organize the findings around three main points: the problems identified, the techniques employed and the benefits obtained.