A recent study is calling for a reconsideration of fashion education to ensure students are prepared with the data science and data analysis skills required to flourish in an ever-changing industry.
The research, ‘Are fashion majors ready for the era of data science? A study on the fashion undergraduate curriculums in US institutions,’ conducted by Lora Merryman and Dr Sheng Lu from the University of Delaware, comes as more and more fashion companies are leveraging data science and related business analytics tools to support their daily business operations.
Figure: From supply chain management and inventory control, to sales forecasting, social media and analyzing consumers’ purchasing behaviors, fashion companies are leveraging data science to improve.
From supply chain management and inventory control, to sales forecasting, social media and analyzing consumers’ purchasing behaviors, fashion companies are leveraging data science to improve or fundamentally change how they create new products.
For example, some fashion companies have begun to integrate data analytics and machine learning in their apparel design process. Well-known fashion icons, such as Gap Inc, have attempted to remove the “creative director” position and instead use data scientists to design new products.
The combination of data science and fashion has attracted many new players, especially technology companies, to enter the fashion business. These tech newcomers, such as EDITED, Trendalytics and Style Sage, provide big-data based analytics tools that help conventional fashion brands and retailers more powerfully and effectively analyze their sales, identify market-popular styles, trends, textile materials, and design product assortment and pricing strategies for their target consumers.
Data science is shifting the fashion job market
Not only is the increasing use of data science changing how fashion brands and apparel retailers design, merchandise, market, and deliver their products, but it also impacts the skillsets companies now expect and demand from their talent.
On the one hand, the growing use of data science is creating new types of jobs that did not exist in the past. An analysis of job openings by US fashion brands and retailers posted on the Business of Fashion (BOF) from January 2019 to July 2020 shows that job titles such as “data editor,” “data scientists,” and “smart inventory manager” were among the most in-demand.
Meanwhile, with the widespread use of data science in almost all aspects of a fashion company’s business operations, even the expectation for traditional “merchandising” and “design” positions are gradually adding new data-related requirements.
Fashion education in the US
As one of the most popular college majors among Generation Z, over 50 undergraduate fashion programs are currently offered by US-based higher education institutions. These college programs typically provide Bachelor of Science (BS) or Bachelor of Art (BA) degrees that concentrate on the design, making, or merchandising of fashion, apparel and textile products.
Pursuing a career in the fashion industry after graduation is among the strongest motivations for students enrolled in an undergraduate fashion program.
Reform fashion education in the era of data science
Even though the fashion industry and the fashion job market are turning more data-intensive, the study finds that fashion students still have minimal opportunities to play with numbers.
Fashion students in US colleges are typically required to take only 2-3 mathematics, statistics, and merchandising courses that include some quantitative data analysis components. However, there are almost no fashion courses directly addressing data science or data analysis.
The study also finds that design-oriented fashion programs, in particular, need to shift the culture of avoiding “math and numbers” and instead create more opportunities for students to play with data and improve their quantitative reasoning skills.
Fashion students’ data processing and data analysis software skills could be improved through stronger industry-academic partnerships.
The authors also suggest launching new interdisciplinary fashion programs that target fast-growing but non-traditional jobs in the fashion industry, such as fashion data scientists. These new programs could also appeal to students interested in the science, technology, engineering, and mathematics (STEM) discipline, resulting in an expanded and more diverse student body of fashion majors.
