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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-04202021-090311


Tipo di tesi
Tesi di laurea magistrale
Autore
PIERUZZINI, NICOLA
URN
etd-04202021-090311
Titolo
Supply Chain Cockpit: Novel Functionalities for Logistics Monitoring
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Prof. Guidotti, Riccardo
Parole chiave
  • business intelligence
  • data
  • delivery flow
  • end-to-end analysis
  • Kering
  • lead time
  • logistics
  • monitoring
  • Power BI
  • reporting
  • stock
  • supply chain
Data inizio appello
07/05/2021
Consultabilità
Non consultabile
Data di rilascio
07/05/2091
Riassunto
This study regards the supply chain analysis of Kering, a multinational group in the luxury fashion sector. Specifically, the company has a structured delivery flow that goes from its factories to the stores, and asked for a business intelligence app to keep track of its behaviour. The tool, called Supply Chain Cockpit, works as a repository of business intelligence reports. Each of them corresponds to a supply chain related topic that makes a report available, and consists of an interactive dashboard with a set of data visualizations that summarizes the KPIs of the selected argument. Aim of this thesis is to explore the Supply Chain Cockpit’s features, and grasp the complex data management process that led to its release. From the creation of the data models to the characteristics of the dashboards, and to the business insights they provide to the users. Specifically, after a general overview on the company’s delivery flow, the focus is on three topics: End-to-End Performance, Central Warehouse Performance, and Store Stock Analysis. The building process and features of the related reports are investigated, as they include all the main aspects of the analysis that has been performed for the rest of the supply chain, too. Timing and quantities are the main analysis dimensions considered. The final outcome well summarizes the journey over the company’s logistics network, and the articulated data processing that is necessary to track it and ensure its reliability.
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