Decision Support System as Solution of Business Intelligence for Retail Organisations in Information Technologies Market

• Autor(a) principal: Silva, Eduardo Sérgio Azevedo
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/15553

Today successful inventory management is a dynamic activity and a balance between the use of basic techniques which are easy to use and give consistent results, and sophisticated techniques which can give better control if used correctly. The inventory manager has to focus on the simple essential requirement “creating the most profit for the organisation through the best customer service” (Wild 2002). This requirement is detailed as excellent forecasting, low inventory, sales value and small operating costs (Wild 2002). For the high level of service, the manager expects to have the accurate and timely information that it’s required to make informed decisions (Imhoff, Galemmo, and Jonathan 2003). Therefore, nothing better than a Business Intelligence (BI) system based on Data Warehouse (DW) dimensional modelling concept conceived by Doctor Ralph Kimball, who is mainly responsible for the widespread use of multidimensional data marts to support online analytical processing. Understanding the full implications and applications of the BI system in inventory management is a gradual process, but worth the effort because of the tremendous benefits. This document explains and details the implementation of a Decision Support System based on the Microsoft Power BI solution to support inventory classification and forecasting, to assist the work of an inventory manager. In practice, several technologies and approaches for the development of a DW were studied, as well as BI solutions to present the information to the inventory manager. It was also elaborated a study of the methodologies for inventory classification and categorisation, as well as algorithms to automate these analyses. Finally, all the knowledge obtained was applied in developing a seamlessly integrated DW. Also, a set of dashboards and indicators were created to assist the inventory manager decision making.