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Public services management is a fundamental role to public institutions, providing society with proper resources for a better quality of life. Local characteristics should be considered during public policies planning; however, generalizations are adopted to elaborate studies, overlooking these characteristics. Our objective was to apply a geostatistical analysis into the public services of Campo Mourão, Paraná State. The number of residents per census tracts lacking in water supply, sewage collection, waste collection, street lighting, electricity, and paving was found based on 2010 Census data. The spatial distribution of these data with the software ArcGIS 9.3 enabled the examination of these characteristics via the Cluster and Outlier method, through the Anselin Local Moran's I spatial analysis module, that identified hotspots and coldspots. As a result, it was found that Campo Mourão is satisfactorily supplied with electricity distribution services and waste collection with only 0.5% of absence in the census tracts. The sewage collection by the general network was the most absent service with 37% absence rate. Parque Industrial I and Jardim Isabel neighborhoods stood out as the most devoid of public services. The Cluster and Outlier Analysis is a subsidy tool for policy-making, which can increase efficiency when providing these services.