Enhancing forecast accuracy and inventory management in the tire industry: a power BI approach at Bridgestone EMEA
In the competitive tire industry, accurate forecasting and efficient inventory management are crucial in order to maintain operational efficiency and customer satisfaction. This thesis focuses on Bridgestone EMEA, a leading tire manufacturer, and has as an objective to enhance forecast accuracy and...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2024 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/428381 |
| Acesso em linha: | https://hdl.handle.net/2117/428381 |
| Access Level: | acceso abierto |
| Palavra-chave: | Automobile industry and trade Automobiles -- Tires Gestion des stocks Forecasting, Bridgestone EMEA, Microsoft Power BI, Slow-moving dead stock, Forecast cycle, Tire Automòbils -- Indústria i comerç Automòbils -- Pneumàtics Gestió d'estocs Àrees temàtiques de la UPC::Economia i organització d'empreses |
| Resumo: | In the competitive tire industry, accurate forecasting and efficient inventory management are crucial in order to maintain operational efficiency and customer satisfaction. This thesis focuses on Bridgestone EMEA, a leading tire manufacturer, and has as an objective to enhance forecast accuracy and inventory management through the development of an analytical tool using Microsoft Power BI. The decision to create this comes after identifying significant discrepancies between forecast cycles at the International Product Code (IPC) level which were impacting operational efficiency and contributing to Slow Moving Dead Stock (SMDS). Comprehensive data from SAP, Excel files, and internal databases were processed to create an interactive Power BI dashboard, enabling detailed comparisons, visualization of forecast variations, and integration of sales data. The Power BI dashboard provides a centralized view, allowing users to identify and analyse forecast discrepancies. This tool offers detailed filters and visualizations, enabling users to look into specific data points, understand the underlying causes of forecast inaccuracies, and take corrective actions. The findings emphasize the importance of accurate forecasting in preventing overstocking and stockouts, which can adversely affect the supply chain and customer satisfaction. With the help of this tool, Bridgestone can focus on areas with the most significant discrepancies, thereby improving operational performance, reducing costs, and maintaining a competitive edge in the tire industry. Recommendations for further improvement include automating data updates, expanding storage capacity, integrating comprehensive databases, and providing continuous user training. This thesis highlights the potential of advanced data analysis and visualization to optimize forecasting and inventory management, demonstrating how Bridgestone can leverage these technologies to enhance strategic decision-making and operational excellence. |
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