Intelligent Dashboard to Optimize the Tax Management in a Town Municipal Government

During the pandemic period, the tax collection in the Municipal Governments in Ecuador held a considerable decrease in money income, suffering reductions in budgets that finance the institutional works in the towns. With several taxes, existence becomes challenging to know which are the ones that citizens stop paying. With the purpose of solving this difficulty, in this work, we developed an intelligent dashboard by using the CRISP methodology. As a first step, we evaluated the tax collections information from the Town Cevallos’ municipal government in Ecuador through the management of administrative processes. The information was obtained from the municipality's official digital databases, documentary collections, and interviews with the departments involved in tax collection. The information released helps us determine the need for an intelligent automated tool to optimize the tax collection process. The tool allowed the understanding of the know-how of the tax collection process in the municipality and the paradigm of information storage. Thus, the tool allows us the detection of errors in databases and the collaborative construction of interactive reports for the management staff. The dashboard implementation allowed to optimize the information management, the depuration, and correction of inconsistent data. In consequence, the time used for this process was 40% compared to the time employed without the dashboard. Finally, the intelligent dashboard gives great support. It reduces the global response time by 87%, obtaining several scenarios based on information entered into the database, contributing to the correct decision-making based on graphical reports.

• Yazar: Castillo, Franklin (author)
• Diğer Yazarlar: Oleas-Orozco, José (author), Saá-Tapia, Fernando (author), Mena-Navas, Carlos (author)
• Materyal Türü: article
• Dil: eng
• Baskı/Yayın Bilgisi: 2022
• Online Erişim: https://link.springer.com/chapter/10.1007/978-3-031-19682-9_34; https://hdl.handle.net/20.500.14809/4450