Abstract
The proposal of a Corporate Governance Model called Service-Focused Operation Methodology (MOCA) was carried out, applied in Public and Private Partnerships (PPP) to improve services quality offered by the Brazilian states. This PPP model enabled several Service Center (in portuguese Central de Atendimento—CA) implementation projects supported by several multidisciplinary knowledge areas that involve projects and governments. However, this article explored an aspect of how a MOCA’s use with new technologies embedded in projects provide continuous improvements in results. In this case, for example, a demand study was applied to Planning and Control of Operations (PCO) in a use of Research and Development (RD MOCA applied in PCO; obtained from stabilized proof of concepts; providing data collection and more accurate performance information in each CA, collected directly by an ERP used. From these data, the design of service production lines was performed using the following methodologies: (1) Descriptive Statistics, (2) Temporal Series and (3) Temporal Underground Neural Networks (ANNT). A Temporal Neural Networks (ANNT) was obtained, using recursive corrections in demand balancing by attendant performance. Using these technologies, a more accurate performance forecast to estimates attendants work was achieved in order to obtain a more realistic operational planning.
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