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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