This thesis examines how the digital transformation of retail operations can generate measurable benefits, focusing on the case of Philip Morris International (PMI) and the use of data analytics. After mapping current practices (heavy reliance on Excel, information silos, manual validations, alignment delays), the study defines the problem of data visibility and integration across the lifecycle of retail projects (openings, refurbishments, relocations). The proposed solution is a Digital Retail Management Platform that unifies information flows, workflows, and collaboration—evolving from the iSquare environment toward Nooal—with a standard data model, upstream validations, event-driven notifications, and integrated dashboards. A KPI framework is presented to measure impact: operating and deployment costs (e.g., cost per m², budget variance), project efficiency (lead time, on-time rate), supplier performance, and predictive indicators (forecast accuracy, delay/overrun risk). The methodology combines document analysis and internal data, semi-structured interviews with project managers and technical stakeholders, and reporting prototypes using synthetic data. Expected results include reduced errors and consolidation time, greater decision transparency, and enhanced predictive capabilities for planning. The thesis discusses limitations (generalizability, historical data availability) and offers recommendations for adoption, integration with existing systems, and continuous improvement.
Questa tesi analizza come la trasformazione digitale delle operazioni retail possa generare vantaggi misurabili, con focus sul caso Philip Morris International (PMI) e sull’uso dell’analitica dei dati. Dopo aver mappato le pratiche correnti (uso esteso di Excel, silos informativi, validazioni manuali, ritardi di allineamento), il lavoro definisce il problema di visibilità e integrazione dei dati lungo il ciclo di vita dei progetti retail (aperture, ristrutturazioni, rilocalizzazioni). La soluzione proposta è una Digital Retail Management Platform che unifica flussi informativi, workflow e collaborazione, evolvendo dall’ambiente iSquare verso Nooal con data model standard, validazioni a monte, notifiche/eventi e dashboard integrate. Viene presentato un framework di KPI per misurare l’impatto: costi operativi e di deployment (es. costo per m², varianza di budget), efficienza progettuale (lead time, on-time rate), performance fornitori e indicatori predittivi (accuratezza forecast, rischio ritardo/overrun). La metodologia combina analisi documentale e dati interni, interviste semi-strutturate a project manager e stakeholder tecnici e prototipi di reporting con dati sintetici. I risultati attesi includono riduzione degli errori e dei tempi di consolidamento, maggiore trasparenza decisionale e capacità predittiva per la pianificazione. Si discutono limiti (generalizzabilità, disponibilità storica dei dati) e si formulano raccomandazioni per adozione, integrazione con sistemi esistenti e miglioramento continuo.
The Role of Data-Driven Insights in Digital Retail Transformation: The Case of Philip Morris International
SANTONI, VALERIO
2024/2025
Abstract
This thesis examines how the digital transformation of retail operations can generate measurable benefits, focusing on the case of Philip Morris International (PMI) and the use of data analytics. After mapping current practices (heavy reliance on Excel, information silos, manual validations, alignment delays), the study defines the problem of data visibility and integration across the lifecycle of retail projects (openings, refurbishments, relocations). The proposed solution is a Digital Retail Management Platform that unifies information flows, workflows, and collaboration—evolving from the iSquare environment toward Nooal—with a standard data model, upstream validations, event-driven notifications, and integrated dashboards. A KPI framework is presented to measure impact: operating and deployment costs (e.g., cost per m², budget variance), project efficiency (lead time, on-time rate), supplier performance, and predictive indicators (forecast accuracy, delay/overrun risk). The methodology combines document analysis and internal data, semi-structured interviews with project managers and technical stakeholders, and reporting prototypes using synthetic data. Expected results include reduced errors and consolidation time, greater decision transparency, and enhanced predictive capabilities for planning. The thesis discusses limitations (generalizability, historical data availability) and offers recommendations for adoption, integration with existing systems, and continuous improvement.| File | Dimensione | Formato | |
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Thesis Santoni V.pdf
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Descrizione: Questa tesi analizza come la trasformazione digitale delle operazioni retail possa generare vantaggi misurabili, con focus sul caso Philip Morris International (PMI) e sull’uso dell’analitica dei dati.
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https://hdl.handle.net/20.500.14239/31024