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Implementação de ferramentas de gestão da informação na cadeia de abastecimento da Iservices
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Resumo(s)
A crescente complexidade e imprevisibilidade dos diferentes cenários das cadeias de abastecimento atuais obriga as organizações a adotarem práticas mais robustas baseadas em dados para a gestão das suas cadeias de abastecimento. Esta investigação incide sobre a empresa Iservices, especializada e dedicada à reparação e comercialização de acessórios e equipamentos tecnológicos. O principal objetivo é analisar de que forma, ferramentas como o Power BI e o Python podem contribuir para a tomada de decisão visando a análise de custos operacionais na sua cadeia de abastecimento e de que forma podem ser reduzidos. A problemática central reside na necessidade de melhorar o desempenho da Cadeia de Abastecimento da empresa, reduzindo desperdícios, otimizando recursos e apoiando a tomada de decisão com base em indicadores de performance. A metodologia adotada neste trabalho será a Design Science Research (DSR), integrando elementos de análise na recolha de dados qualitativos e quantitativos, de forma a assegurar uma abordagem abrangente e rigorosa à problemática escolhida. A componente qualitativa consistirá na análise documental de relatórios internos, mapas operacionais, registos de processos logísticos e outros elementos relevantes. Será também realizada observação direta das atividades desenvolvidas pelos colaboradores da Iservices, com especial foco nas áreas de logística, compras e técnicos de reparação, de modo a compreender os fluxos operacionais e identificar, in loco, potenciais fontes de ineficiência. Por sua vez, a componente quantitativa envolverá a análise dos dados extraídos das diversas fontes de dados da empresa, onde na sua génese estão registos operacionais históricos relacionados com níveis de inventário, vendas, compras, custos logísticos, registos de operação e outros indicadores críticos da cadeia de abastecimento. Serão utilizadas ferramentas para recolha, tratamento e analise dos dados, entre os quais destaca-se o Power BI para visualização e Python para os demais processos mencionados, com o objetivo de quantificar o impacto para os diferentes cenários de redução de custos sobre a área financeira e operacional. Com este trabalho, pretende-se contribuir para a melhoria dos mecanismos de controlo e otimização de custos operacionais em empresas com estruturas logísticas complexas, como é o caso da Iservices, através da integração de boas práticas de gestão, ferramentas tecnológicas e análise financeira orientada à tomada de decisão, centrada num estudo de caso. Na Iservices, a aplicação direta das ferramentas trouxe maior capacidade de decisão, maior rapidez e visibilidade do pipeline de informação. Os resultados esperados incluem a identificação de oportunidades concretas de redução de custos, a criação de dashboards para a cadeia de abastecimento e a proposta de medidas otimizadas com impacto direto na performance da cadeia de abastecimento da Iservices. Por via da aplicação do artefacto, obteve-se em termos maior rotação do stock, melhor tomada de decisão para o equilíbrio entre o principal ativo circulante na empresa e a aplicação de recursos e a redução de custos na área dos transportes.
The growing complexity and unpredictability of the various scenarios faced by today’s supply chains compel organisations to adopt more robust, data-driven practices for managing their supply chains. This research focuses on Iservices, a company specialising in the repair and sale of technological accessories and devices. The main objective is to analyse how tools such as Power BI and Python can support decision-making aimed at analysing operational costs in its supply chain and how these costs can be reduced. The central issue lies in the need to improve the performance of the company’s supply chain by reducing waste, optimising resources, and supporting decision-making based on performance indicators. The methodology adopted in this work will be Design Science Research (DSR), integrating analytical elements into the collection of qualitative and quantitative data, so as to ensure a comprehensive and rigorous approach to the chosen problem. The qualitative component will consist of documentary analysis of internal reports, operational maps, records of logistics processes, and other relevant elements. Direct observation will also be carried out of the activities performed by Iservices employees, with particular focus on logistics, procurement, and repair operations, in order to understand operational flows and identify, in situ, potential sources of inefficiency. The quantitative component, in turn, will involve the analysis of data extracted from the company’s various data sources, originating in historical operational records related to inventory levels, sales, purchasing, logistics costs, operational logs, and other critical supply chain indicators. Tools will be used for data collection, processing and analysis, namely Power BI for visualisation and Python for the remaining processes mentioned, with the purpose of quantifying the impact of the different cost-reduction scenarios on the financial and operational areas.. For the literature review, a comprehensive approach will be used, involving the collection and critical analysis of selective scientific studies with broad coverage and sourced from leading academic databases, focusing on topics such as supply chain management, supply chain cost analysis, Python, Power BI, KPIs, financial management, and Business Intelligence applied to the supply chain. The main objective is to underpin the argumentation of the topic and, likewise, to broaden current knowledge of the state of the art at the time of writing. With this work, the aim is to contribute to improving control mechanisms and the optimisation of operational costs in companies with complex logistical structures, such as Iservices, through the integration of management best practices, technological tools, and decision-oriented financial analysis, centred on a case study. The expected results include the identification of concrete cost-reduction opportunities, the creation of supply chain dashboards, and the proposal of optimised measures with a direct impact on the performance of Iservices supply chain.
The growing complexity and unpredictability of the various scenarios faced by today’s supply chains compel organisations to adopt more robust, data-driven practices for managing their supply chains. This research focuses on Iservices, a company specialising in the repair and sale of technological accessories and devices. The main objective is to analyse how tools such as Power BI and Python can support decision-making aimed at analysing operational costs in its supply chain and how these costs can be reduced. The central issue lies in the need to improve the performance of the company’s supply chain by reducing waste, optimising resources, and supporting decision-making based on performance indicators. The methodology adopted in this work will be Design Science Research (DSR), integrating analytical elements into the collection of qualitative and quantitative data, so as to ensure a comprehensive and rigorous approach to the chosen problem. The qualitative component will consist of documentary analysis of internal reports, operational maps, records of logistics processes, and other relevant elements. Direct observation will also be carried out of the activities performed by Iservices employees, with particular focus on logistics, procurement, and repair operations, in order to understand operational flows and identify, in situ, potential sources of inefficiency. The quantitative component, in turn, will involve the analysis of data extracted from the company’s various data sources, originating in historical operational records related to inventory levels, sales, purchasing, logistics costs, operational logs, and other critical supply chain indicators. Tools will be used for data collection, processing and analysis, namely Power BI for visualisation and Python for the remaining processes mentioned, with the purpose of quantifying the impact of the different cost-reduction scenarios on the financial and operational areas.. For the literature review, a comprehensive approach will be used, involving the collection and critical analysis of selective scientific studies with broad coverage and sourced from leading academic databases, focusing on topics such as supply chain management, supply chain cost analysis, Python, Power BI, KPIs, financial management, and Business Intelligence applied to the supply chain. The main objective is to underpin the argumentation of the topic and, likewise, to broaden current knowledge of the state of the art at the time of writing. With this work, the aim is to contribute to improving control mechanisms and the optimisation of operational costs in companies with complex logistical structures, such as Iservices, through the integration of management best practices, technological tools, and decision-oriented financial analysis, centred on a case study. The expected results include the identification of concrete cost-reduction opportunities, the creation of supply chain dashboards, and the proposal of optimised measures with a direct impact on the performance of Iservices supply chain.
Descrição
Palavras-chave
Business Intelligence Custos Supply Chain Costs