DataCities in Practice 2024 – Linking Data Analytics to Routine City Decisions & Policymaking: A case of Property & Street Parking Revenue Mobilization in Fort Portal City, Uganda

In today’s fast-paced digitalized world, generated data resources and data analytics supported by artificial intelligence (AI) capabilities, are transforming the way cities engage residents, plan and govern the urbanization development process (Ferhati et al., 2024; Almaz et al., 2024; Herath & Mittal, 2022). Fort Portal is one of the newest cities focused on developing as a tourists’ hub in Uganda, committed to piloting a few data & AI use cases in pursuit of this dream. For example, the city authority is harnessing the power of data and desires to optimize AI capabilities through the Integrated Revenue Administration System (IRAS). The core strength of IRAS lies in its ability to streamline and automate critical processes such as taxpayer registration, property assessments, and revenue collection. Before this system was implemented, the city’s revenue collection was often manual, time-consuming, and prone to errors. By digitizing these functions, Fort Portal City has unlocked a new sphere of data use for transparency and efficiency in managing its property revenue generation, in particular.

This dynamic digital data platform is more than just a tool for collecting local revenue. According to the DataCities assessment of the facility, it was found to have considerable untapped potential to support evidence-informed rapid decisions, local tax policymaking, stakeholders’ engagement, mobilization for increased awareness on city’s economic resilience, if optimized well. By optimizing IRAS’ performance through instituting data integrity standards for real-time data and AI capabilities integration into city revenue governance and management, the city will not only be streamlining administrative processes, but also ensuring that decisions are based on accurate, up-to-date information that benefits everyone from residents, utility service providers/stakeholders to policymakers (Huang et al., 2023; PcW, 2024).

Download full article from here; Revenue Data Analytics  – FP (Jan 2025)

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Ben Chilwell

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Ben Chilwell

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