Can Artificial Intelligence Combat Oversupply and Minimise Deadstock in Fashion?
The McKinsey Notes From The AI Frontier report quantifies the benefits of AI for retail as being mostly in marketing and sales (targeting customers with the right products and boosting conversion) and supply chain and manufacturing (manufacturing the right product in the right quantity and making it available at the right time). While this may sound basic, it’s the current fast fashion business model’s inability to get this right that is causing overstock and catastrophic resource and waste consequences.
How can AI help to cut down on oversupply of stock and thereby reduce the environmental impact of unsold fashion? One of the key ways is by capturing data through online sales based on geographical areas to determine the types of products that are on demand (and those that aren’t) in specific locations. A prime example of this is the Nike Live store ‘Nike by Melrose’ in West Hollywood, which is a fusion of online and offline stores. The first of its kind, the store requires shoppers to sign up to the Nike Plus app in order to unlock the services and perks available in the store. In signing up, the shopping behaviour and preferences of each customer are known to Nike, allowing it to only stock what local shoppers want. No overstock and no need to have regular sales to get rid of stock that wasn’t right for the local customers. This data feeds back to the manufacturing systems and influences the styles and quantities manufactured.
Casting the net wider to take in global shopping preferences and real-time purchasing behaviour, The Trending Store, which opened in London’s Westfield Shopping centre this week, is using AI to analyse social media data to extrapolate the ‘top 100 fashion items’. The trending products, which span high-street and designer looks across fashion, accessories and footwear, are then collected each morning by a team of stylists from the retail stores at Westfield London. The data analytics are being performed by NextAtlas, who track 400,000 early adopters spread across 1,000 cities worldwide to determine the top 100 items. Screens in The Trending Store show exactly where each trend originates from, so shoppers can see which city or country is influencing the popularity of the item. This is perhaps the first foray into shopping centres providing AI-driven multi-brand solutions that helps get trending styles and colours in front of customers at the right time.
It bears noting that these are reactionary solutions that require linked-up data and transparency across the supply chain to genuinely reduce overstock and deadstock – that is to say, the data should ultimately drive the design and manufacturing process to ensure that only the product that is ‘needed’ is manufactured. As fast fashion retailers struggle to manage the vast quantity of products they manufacture globally, this data could allow retailers to make smarter and more sustainable decisions. However, digitalisation of the entire supply chain (allowing the capture of data at all points from the initial design and manufacturing to global sales) is necessary in order to fully harness and act on this powerful data. Watch this space.
What to do about overconsumption? Listen as Clare Press and Kate Fletcher call for a radical fashion rethink in the latest episode of Wardrobe Crisis podcast.
Read about the Sustainability of the Fashion Industry Inquiry.
Not sure where to start when it comes to ethical fashion? Read our guide to dressing ethically.