Municipal Use of Predictive Analytics for Service Allocation

Abstract

Background: Recent developments involving predictive analytics have made implementation quality, oversight, and administrative capacity central policy concerns.

Objective: The analysis examined how policy relating to predictive analytics operated in practice and whether differences in capacity and oversight were associated with outcomes in relation to municipalities.

Methods: Across 8 jurisdictions or institutional settings, legal and policy sources were combined with organizational evidence and, when available, key-informant material. Comparative coding focused on authority, coordination, transparency, safeguards, enforcement, and implementation capacity.

Results: Variation in predictive analytics clustered into three identifiable patterns. The stronger cases paired clear mandates with formal coordination and accessible review, producing a 18% advantage in the composite implementation score. Delay and inconsistent enforcement were concentrated in settings with fragmented responsibility.

Conclusion: The results shift attention from whether rules on predictive analytics exist to how those rules are administered in practice. This means that responsible AI adoption requires governance arrangements that can be implemented consistently across agencies, not merely high-level principles.

Study design: case-comparison study.

Publication history: Originally published in print on 15 June 2023, Volume 3, Article 15. Online abstract record added on 16 September 2026. Full-text PDF will be added when the digital galley is ready.