How Zara Really Grew Into the World s Largest Fashion Retailer
JeanFrancoisPuget 2700028FGP Visits (31874)
The New York Times recently published an interesting paper on How Zara Grew Into the World’s Largest Fashion Retailer. The paper describes the Fast Fashion business model that fuels Zara' growth. What the paper doesn't say is that mathematical optimization played a key role in enabling this business model.
More precisely, Zara worked with MIT and UCLA on several business problems. There are few publications, I pasted their abstracts below.
Clearance Pricing Optimization for a Fast-Fashion Retailer
Fast-fashion retailers such as Zara offer continuously changing assortments and use minimal in-season promotions. Their clearance pricing problem is thus challenging because it involves comparatively more different articles of unsold inventory with less historical price data points. Until 2007, Zara used a manual and informal decision-making process for determining price markdowns. In collaboration with their pricing team, we designed and implemented since an alternative process relying on a formal forecasting model feeding a price optimization model. As part of a controlled field experiment conducted in all Belgian and Irish stores during the 2008 Fall-Winter season, this new process increased clearance revenues by approximately 6%. Zara is currently using this process worldwide for its markdown decisions during clearance sales.Full paper available a: http
Zara Uses Operations Research to Reengineer Its Global Distribution Process
Abstract: Overcoming significant technical and human difficulties, Zara recently deployed a new process that relies extensively on sophisticated operations research models to determine each inventory shipment it sends from its two central warehouses to its 1,500 stores worldwide. By taking a retail size-assortment view of a store's inventory, the model incorporates the link between stock levels and demand to select store replenishment quantities. Through a rigorous, controlled field experiment, we estimate that this new process has increased sales by 3–4 percent; this corresponds to estimated profits of approximately $233 million and $353 million in additional revenues for 2007 and 2008, respectively.
Full paper available at: http
Inventory Management of a Fast-Fashion Retail Network
Working in collaboration with Spain-based retailer Zara, we address the problem of distributing, over time, a limited amount of inventory across all the stores in a fast-fashion retail network. Challenges specific to that environment include very short product life cycles, and store policies whereby an article is removed from display whenever one of its key sizes stocks out. To solve this problem, we first formulate and analyze a stochastic model predicting the sales of an article in a single store during a replenishment period as a function of demand forecasts, the inventory of each size initially available, and the store inventory management policy just stated. We then formulate a mixed-integer program embedding a piecewise-linear approximation of the first model applied to every store in the network, allowing us to compute store shipment quantities maximizing overall predicted sales, subject to inventory availability and other constraints. We report the implementation of this optimization model by Zara to support its inventory distribution process, and the ensuing controlled pilot experiment performed to assess the model's impact relative to the prior procedure used to determine weekly shipment quantities. The results of that experiment suggest that the new allocation process increases sales by 3% to 4%, which is equivalent to $275 M in additional revenues for 2007, reduces transshipments, and increases the proportion of time that Zara's products spend on display within their life cycle. Zara is currently using this process for all of its products worldwide.Full paper available at: http
Zara team and their academic colleagues were Edelman award finalists.
Each year, the Edelman Award Committee sponsored by INFORMS selects the five or six best entries to advance to the Franz Edelman Award final selection. These five or six entries are called the
Being an Edelman finalist means you join a very selective group of extremely successful optimization practitioners, as witnessed by the extreme return on investment they enabled.
Not only are these interesting applications of mathematical optimization, but the fact that they are powered by our CPLEX product makes me proud of CPLEX team!
Edited on Nov 17 2012. Edelman award piece added.
This post was motivated by this entry from Anna Nagurney