Coordination of Inventory Distribution and Price Markdowns for Clearance Sales at Zara

Abstract

Zara holds a clearance period for several weeks after each of its two annual selling seasons. Due to restrictions in shipping capacity, allocation decisions for the remaining warehouse inventory start 4–6 weeks prior to the clearance period. Our work addresses the problem of dynamically coordinating inventory and pricing decisions for unsold merchandise during the last month of the regular season and then clearance sales. The inventory allocation prior to markdowns is particularly challenging because it is a large-scale optimization problem and countries “compete” for scarce inventory. Moreover, there are many business rules that must be satisfied. Until recently, the decision process used by Zara for end-of-season inventory allocation and clearance pricing was essentially manual and based on managerial judgment. We propose a model-based approach that builds on a deterministic approximation. The deterministic problem is still too large so it is further broken down into an aggregate master plan and a store-level model per-country with feedback recourse between the two levels. After a working prototype of the new tool was completed, we performed a controlled field experiment during the 2012 summer clearance to estimate the model’s impact. The controlled experiment showed that the model increased revenue by 2.5%, which is equivalent to $24M in additional revenue. Given that unsold inventory is sunk at the time of clearance sales, the additional revenue translates directly into profits. The implementation of the tool coincided with the launch of Zara’s online portal. We discuss how the model-based process was adjusted to accommodate this new channel.