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          Fashion by numbers

          By Gan Tian | China Daily | Updated: 2013-09-02 07:36

           Fashion by numbers

          Dresses from Alice by Temperley and jeans from Current/Elliott are must-have items according to Shangpin.com. Photos provided to China Daily

          The job of buying clothes might seem glamorous, but as Gan Tian discovers, it has more to do with a spreadsheet than the catwalk.

          What makes a good fashion buyer? Glamour? Being fashion savvy?

          The mundane truth is, the job might be best suited to geeky people who are specialized in numbers and data.

          Winnie Foon, the fashion buyer who used to work with prestigious fashion retailers Lane Crawford, Seibu and I.T, joined local e-commerce website Shangpin.com in 2011. She is now looking for new talent to join her team.

          "Though this job is comparatively well-paid, there are not many qualified people in this market," Foon says.

          As a veteran fashion buyer for nearly 20 years, Foon says the most important skill for the job is the ability to make connections and predictions from a large amount of numbers, data and charts.

          She cites an example of the importance of this ability. At the end of last year, Foon's team bought X number of blue skirts for the company, but only Y number had sold by the end of summer. When she plans this year's purchasing, she will only buy Y number of skirts.

          The skirt of this season should be similar in style but different in color, she says. The simple X and Y example will become much more difficult when multiplied by numerous items, taking in different colors, styles, genres, and other fashion catalogues.

          Xue Shaohuan agrees. The 29-year-old Beijing local, who frequently flies to Paris, Milan, London and New York to buy garments from independent designers, has two stores in Beijing and Shanghai.

          "For independent fashion buyers, profit-making products are much more welcoming. This requires good ability in numbers and data," she says.

          Related:

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