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dc.contributor.advisorTena Blázquez, Antonioes-ES
dc.contributor.authorPelayo Ruiz, Águedaes-ES
dc.contributor.otherUniversidad Pontificia Comillas, Facultad de Ciencias Económicas y Empresarialeses_ES
dc.date.accessioned2025-12-12T12:20:00Z-
dc.date.available2025-12-12T12:20:00Z-
dc.date.issued2026es_ES
dc.identifier.urihttp://hdl.handle.net/11531/107640-
dc.descriptionMáster Universitario en Administración de Empresas (MBA)es_ES
dc.description.abstractThis project addresses a core operational challenge faced by Ailin, a Spanish home-based diagnostic kit company, the absence of a structured, data-supported approach to inventory management and demand forecasting. As the company scales across seven European markets, its reliance on manual processes generates increasing friction across purchasing, warehousing, and customer fulfillment. Through process mapping, bottleneck analysis and a benchmarking of six inventory management solutions, the project diagnoses the root causes of these inefficiencies and defines sixteen functional requirements for a technology solution suited to Ailin's operational context and regulatory environment. The recommendation is a phased approach. First an immediate combination of the e-commerce platform's inventory module, Power BI, and automated Excel, delivering real-time visibility and analytical capability within six months at an estimated total cost of ownership of 18.700 euros; followed by a medium-term migration to SAP Business One once defined operational thresholds are met. Financial modelling under both standard and conservative scenarios confirms Phase 1 is viable without external financing, while Phase 2 remains sustainable under standard conditions. Together, the two phases provide a realistic, evidence-based path from Ailin's current manual model toward a fully integrated, compliance-ready inventory infrastructure.es-ES
dc.description.abstractThis project addresses a core operational challenge faced by Ailin, a Spanish home-based diagnostic kit company, the absence of a structured, data-supported approach to inventory management and demand forecasting. As the company scales across seven European markets, its reliance on manual processes generates increasing friction across purchasing, warehousing, and customer fulfillment. Through process mapping, bottleneck analysis and a benchmarking of six inventory management solutions, the project diagnoses the root causes of these inefficiencies and defines sixteen functional requirements for a technology solution suited to Ailin's operational context and regulatory environment. The recommendation is a phased approach. First an immediate combination of the e-commerce platform's inventory module, Power BI, and automated Excel, delivering real-time visibility and analytical capability within six months at an estimated total cost of ownership of 18.700 euros; followed by a medium-term migration to SAP Business One once defined operational thresholds are met. Financial modelling under both standard and conservative scenarios confirms Phase 1 is viable without external financing, while Phase 2 remains sustainable under standard conditions. Together, the two phases provide a realistic, evidence-based path from Ailin's current manual model toward a fully integrated, compliance-ready inventory infrastructure.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United Stateses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/es_ES
dc.subject.otherH0Ees_ES
dc.titleSin título establecido.es_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.keywordsinventory automation, demand forecasting, diagnostic kits, ERP implementation, online store platform.es-ES
dc.keywordsinventory automation, demand forecasting, diagnostic kits, ERP implementation, online store platform.en-GB
Aparece en las colecciones: TFG, TFM (temporales)

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