Merchandise Planning Models for Fashion Retailing

  • Kumar Rajaram
Part of the International Series In Operations Research & Mana book series (ISOR, volume 119)

Merchandise planning is the process conducted by a retailer to ensure that the right product is available to the customer at the right place, time, quantity and price. This process involves selecting the products the retailer will carry and determining the purchase quantities of these products. Merchandising has become more complex because of changes in the retail industry such as consolidation, global sourcing, higher levels of competition, increasing product variety, reduced life cycles and less predictable demand. Enhancements in information, manufacturing and distribution technology offer potential to reduce the large markdowns due to excessive inventory and lost sales opportunity due to sellouts currently prevalent in this industry. In this chapter, we study two problems in retail merchandising. In the first problem, we develop a methodology to improve the accuracy of merchandise testing by choosing how many and at which stores to test new products and how to extrapolate test sales into a forecast for the entire season across the chain. In the second problem, we consider replenishment based on actual sales, a strategy that can be employed by the retailer to minimize inventory risk associated with an assortment of products. In both these problems, we develop models that are compared to existing practices at these retailers using real sales data. Comparing our techniques to current practices, we found they could reduce markdowns due to excessive inventory and lost margins due to stockouts enough to increase profits by over 100% in each application. General insights on improving this process and future research directions are described.


Forecast Error Test Store Forecast Revision Backorder Cost Fashion Product 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Kumar Rajaram
    • 1
  1. 1.Decisions, Operations and Technology ManagementUCLA Anderson SchoolLos AngelesUSA

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