Monday, September 9, 2013

Customer Analytics and Inventory Management

Professor Zak’s two competing supply chain models have been the steel manufacturer and the boutique clothing designer.  The former can exchange responsiveness to changes in consumer demand for efficiency; the latter is much more concerned about its ability to meet or project the vicissitudes of fashion.  This article illustrates how the latter- a clothing retailer- uses analytics to keep abreast of and predict the latest trends and adjust inventory accordingly.

The company, ModCloth, tracks the purchasing habits of categories of customers (citing, for instance, that plus-size customers buy 17% more items per order than do ordinary customers).  ModCloth also seeks customer input as to the sorts of dresses they would buy; these data helps determine the company’s orders and inventory holdings.    

This analytic capacity allows the company’s inventory to keep pace with its “very rapid supply chain.”  By shaping its orders to fit the ever-changing demands of its customer base,  ModCloth can both reduce the risk of obsolescence and minimize its stock of materials.

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