Could fashion forecasting technology help fashion’s overproduction problem?

Every year, 15-45 billion items of clothing produced go to waste, mostly ending up in landfills or incinerated.

Lately, the topic of overproduction has become more notorious due to new laws and the increase in consumers’ demands for more responsible actions. However, overproduction in fashion is not something new. It has been a long-lasting, deep-rooted problem for brands, being both a huge sustainability problem and a costly commercial one. 

To help brands solve this problem, WGSN has teamed up with OC&C Strategy Consultants to reveal how trend forecasting can be used to tackle the issue head-on - significantly improving margins and efficiency and reducing wastage.


Download the report for need-to-know insights on how data can help your brand connect commercial and sustainability agendas, and better align with future demand.

In the report

  • Case study on how a mass-market retailer could have improved margin by £1m-1.5m in its Women’s Skinny Jeans line using more accurate data.
  • How by implementing AI informed models, brands can be confident in their decision-making and weave together commercial and sustainability goals.
  • How shorter supply chains and stock aggregation are enabling flexibility.

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Minimise waste

WGSN TrendCurve+ is the only predictive analytics product that combines unrivalled data sources across social, search, shelf, shows and sentiment with advanced machine-learning to tell you which trends to invest in, how heavily and when. 

With 90%+ forecasting accuracy, TrendCurve+ can help you make assertive decisions on when to pull back from a trend to avoid overstock and trade more sustainably, with foresight on when trends are projected to peak and decline.

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