Marico Ltd.: Distribution Network Optimization

On July 1, 2020, the co-head of the logistics and planning department at Marico Ltd., based in India, was reviewing reports on various issues related to stock inventory and warehousing. After studying the reports, he found that both lost opportunity and warehousing costs for the company were high. Compounding the problem was the ongoing COVID-19 pandemic, which had added pressure to the company’s impending cost pressures. Initially, Marico Ltd. had thirty-three warehouses. However, after the Government of India introduced the Goods and Service Tax in 2017, various state taxes across the country were eliminated. The new law revolutionized the logistics industry and allowed Marico Ltd. to reduce the number of its warehouses to twenty-five. Could the company further reduce the number of warehouses without adversely impacting service levels?

This exercise can be used to teach supply network design and analysis in courses on supply chain management or logistics management at the postgraduate level in management, industrial management, and engineering programs. The exercise provides an overview of the distribution planning network in a fast-moving consumer goods setting, using clustering and mixed integer linear programming. It uses sensitivity analysis to strengthen the mathematical calculations by evaluating the stability of the mathematical solution, which will provide the final geographic locations for the warehouses. Students can use the data provided in the exercise content and exhibits to understand the methodology execution and the reasons for the choices made. The exercise also provides insights into the issues a business faces when designing a distribution network. Specifically, completing this exercise and assignment questions will allow students to <ul><li>complete an overview and analysis of supply network planning using the spreadsheet software Microsoft Excel and the programming tool Python;</li><li>interpret regression and linear programming outcomes for network design; and</li><li>compare various potential alternatives and recommend a final decision.</li></ul>

• Warehouse location
• Clustering
• Mixed Integer Linear programming
• Distribution management