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Predictive optimization model designed to improve logistics efficiency for Lavazza by identifying cost-effective warehouse locations and distribution strategies, ultimately saving 15% on transportation costs.

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stefagnone/-Optimization-Model-for-Lavazza-s-Logistics-Network

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Project Overview

This project involved developing an optimization model to enhance the logistics network for Lavazza, a leading global coffee producer. The objective was to identify cost-saving opportunities by re-evaluating the network structure and considering the introduction of a satellite warehouse. The model analyzed various scenarios to determine the optimal warehouse configuration, aiming to reduce transportation costs by over 15%.

The analysis focused on:

  • Assessing Lavazza’s existing logistics network and identifying inefficiencies.
  • Utilizing optimization techniques to evaluate the impact of adding a satellite warehouse.
  • Providing actionable insights to improve Lavazza’s operational efficiency and customer satisfaction.

Technologies Used

  • Microsoft Excel: Used for building the optimization model, performing scenario analysis, and visualizing results.
  • PowerPoint: Created a business-oriented presentation to summarize findings, methodology, and recommendations.

Repository Structure

  • Data/: Contains logistics data utilized for the optimization model and cost analysis.
  • Output/: Includes the final report(Lavazza Case.pdf) and presentation file.

Key Insights

  • Introducing a satellite warehouse could reduce Lavazza's logistics costs by approximately 15.36%.
  • The optimization model identified Warehouse 4 as the most cost-effective location for the satellite warehouse, resulting in minimized total logistics costs.
  • The analysis revealed that switching from less-than-truckload (LTL) to full-truckload (FTL) in specific routes could significantly reduce overall expenses.

Instructions

  1. Clone this repository.
  2. Review the logistics data and optimization model details in Data/.
  3. Open and review the final presentation in Output/Lavazza Case.pdf for detailed analysis and business recommendations.
  4. Examine the Excel model (Final_Output_Excel.xlsx) to understand the scenario analysis and cost-saving calculations.

Contact

Connect with me on LinkedIn for more information or explore my other projects on GitHub.

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Predictive optimization model designed to improve logistics efficiency for Lavazza by identifying cost-effective warehouse locations and distribution strategies, ultimately saving 15% on transportation costs.

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