Could fashion forecasting technology help fashion’s overproduction problem?

Overproduction is a long-lasting, deep-rooted problem in the apparel industry. 15-45 billion items of clothing produced every year are wasted, mostly ending up in landfill or incinerated. 

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

Fashion brands tend to use planning and buying models that have an inherent risk of overbuying to reduce the likelihood of products running out of stock. Even with rising prices due to inflation, practices are slow to evolve. 

However, agile, AI-informed buying processes are enabling brands to refine their range in line with consumer demand, operate more efficiently, and therefore drive significant value. 

A case study (2022) reveals how a mass-market retailer could have improved margin by £1m-1.5m in its Women’s Skinny Jeans line if more accurate forecasting data was used.

Buying in line with the decline in market demand would have resulted in 10k-40k fewer units of terminal stock.
 

Findings of the study also reveal five ways in which the fashion industry’s operating model is being disrupted:

1. The trends landscape is shifting, becoming increasingly complex: Consumers engage and transact across multiple channels from physical to digital to social (e.g., TikTok) and beyond. Understanding consumer influences in a more holistic way is crucial to ensuring stock aligns with customer demand.
2. Tech supports efficiency and decision-making: Inflating costs and complexity are driving the need for greater efficiency in operations from design / planning through to depot / supply chain. Technology is critical to unlocking ‘doing more with less’. 
3. Shorter supply chains and stock aggregation are enabling flexibility: Greater flexibility to allocate stock in line with demand is becoming increasingly important to drive efficiencies across channels and markets. 
4. Planning needs to be real-time: Shifting to shorter, more frequent buys more directly linked to demand allows better reaction to trend, management of waste, protection of cash flow and reduction in markdowns.
5. Circularity, rental, and resale: Completely different operating models are gaining traction as brands and consumers lean into sustainability. Resale represents c.7% of market value and significant innovation in circularity taking place. Brands need to consider range requirements for resale in their planning. 

In conducting the research, OC&C utilised WGSN TrendCurve+ data to model the potential for planning and buying improvements. TrendCurve+ is a product from WGSN that combines data sources across social, search, shelf, shows, and sentiment, with advanced machine learning that helps fashion brands invest in the most popular products with 90% forecasting accuracy.

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