Modelo construtivista de apoio à gestão de risco das unidades gestoras municipais para o Tribunal de Contas do Estado de Santa Catarina

• Ano de defesa: 2019
• Autor(a) principal: Garcia, Hemerson José
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Avaliação de desempenho; Gestão de risco; Multricritério; Abordagem construtivista; Unidade gestora municipal; Estudo de caso
• Link de acesso: https://repositorio.animaeducacao.com.br/handle/ANIMA/2868

The management of occurrences of unwanted events is nowadays one of the major concerns of managers. Unlike the management of probabilistic or uncertain events, risk management deals with contexts where unwanted events are somehow disseminated, making it hard to identify and manage through rationalist methods. Santa Catarina State’s Audit Office (TCE/SC) is responsible for risk management in about 1700 management units in the state of Santa Catarina – Brazil and, aiming at the improvement of its monitoring and supervision systems, chose to develop a model to evaluate the risk in municipal units under its jurisdiction to support its decisions. The constructivist approach was adopted in order to ensure a better comprehension of the problem and its singularities. The Knowledge Development Process-Constructivist (ProKnow-C) tools were used in the review of literature and the Multicriteria Decision Aid-Constructivist Methodology (MCDA-C) methodology was utilized in the construction of the model. The model identified four strategic objectives: Accounting/Financing, Budget Execution, Public Politics and Governance Management, which were operationalized following sixty criteria. The model was illustrated for the evaluation of risks in three units, thus evincing its competitive differentials and vulnerabilities, to which were employed improvement measures. This article is a case study of exploratory nature that presents a constructivist procedure in its construction and is proactive when operationalized. As a scientific and empirical contribution, this study stands out by presenting an alternative to the realistic models found in literature, which attempt to manage risks through past behaviors based upon historic data or insurance claims. Such models react after the occurrence of unwanted events. The current proposal works proactively managing the environments from the identification and measurement of the propitious conditions for the occurrence of unwanted events, thus making predictions and acting in an adequate manner to avoid the need for untimely actions.