Optimization of a fast-response distribution network

Inditex is one of the world's largest fashion distributors, operating 3,100 stores in 64 countries; its brands currently include Zara, Pull and Bear, Massimo Dutti, Bershka, Stradivarius, Oysho, Zara Home and Kiddy's Class. The group's flagship company is Zara, which is the world's largest "fast fashion" company: through unique and carefully integrated design, manufacturing and distribution processes, Zara routinely achieves design-to-shelf leadtimes of 6 weeks against an industry average of 6 months, and introduces 11,000 references per season against an industry average of 3,000. Throughout the season, Zara currently ships every new incoming product to all 950 stores comprising its distribution network at the same time. Its operations group has recognized a large opportunity in customizing the assortment of products offered in each store based on local sales, and staggering shipments to stores of each new reference in order to acquire more accurate sales forecast and enable better subsequent inventory allocation decisions. My thesis will detail the development and implementation of new optimization models for dynamically allocating inventory across Zara's distribution network.

Department dc:contributor.department

Leaders for Manufacturing Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Correa, Juan R. (Juan Roza)

Advisor dc:contributor.advisor

• Jérémie Gallien, David Roylance and Felipe Caro.

• Sloan School of Management.
• Materials Science and Engineering.
• Leaders for Manufacturing Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/39596

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/39596