Fashion has an inventory management problem, and it’s only intensified in recent years. Solving these challenges has proven elusive, leaving the industry with billions in unsold stock annually and fuelling a system running on baked-in excess where margin-killing markdowns are the norm.
This is largely due to consumers demanding faster, trend-driven cycles, which reduce lead times and increase the need for brands to accurately forecast demand. Global disruptions, ranging from supply chain delays to unpredictable shifts in consumer behaviour, which stem from events like the pandemic, have also exacerbated forecasting challenges. Traditional demand patterns are no longer reliable, as external factors like unexpected lockdowns, fluctuating consumer spending and the climate crisis have injected further unpredictability. Seasonal volatility has also grown, with more extreme weather events impacting everything from materials sourcing to shipping timelines, making it harder to maintain accurate forecasts.
Can AI help?
A new crop of tech startups has emerged to answer that question, each with its sights set on evolving the Byzantine reality of fashion retail, where critical functions too often rely on error-prone manual data entry and unwieldy spreadsheets. Autone, an AI-powered platform, is one such startup, giving clients like Roberto Cavalli and Courrèges the tools to better forecast demand and optimise stock levels.
Fresh off a $17 million series A funding round led by General Catalyst — a backer of unicorns like Instacart and Airbnb — London-based Autone wants to redefine efficiency for forecasters and demand planners toiling inside fashion, beauty and accessories brands. Born from the first-hand experience of founders Adil Bouhdadi and Harry Glucksmann-Cheslaw during their time at Alexander McQueen, Autone addresses the pain points they encountered managing critical operational functions for the iconic fashion house, where the former — now the startup’s CEO — left as head of decision intelligence, and the latter — who now holds the chief technology officer title — was commercial insights manager.
“We realised that it’s not about creating the best forecast on the planet,” says Bouhdadi. “It’s about giving inventory allocators a platform that tells them which tasks they should execute to achieve their targets and explains why these tasks will accomplish these goals.”
Autone joins a growing number of tech-driven entrants hoping to bring order to fashion’s stock management and demand planning difficulties. Singuli, a notable name in the retail technology sector, similarly offers an AI-powered solution to the perennial challenge of inventory optimisation. Through machine learning, Singuli works with retail clients including Rhone, Cozy Earth and Harper Wilde to accurately forecast demand, streamline stock allocation across multiple channels and automate replenishment, ultimately minimising waste and maximising efficiency. Since it launched in February 2019 and raised a $3.7 million seed round two years later, the startup has been helping businesses manage their stock, which has led to reduced costs, increased sales and enhanced customer satisfaction.
Another emerging player in the retail technology space, three-year-old Prediko has raised at least $5 million to build an AI-powered platform that aims to take the guesswork out of inventory management for e-commerce businesses. Designed specifically for digitally native Shopify merchants, Prediko aims to become a tool for online retailers looking to navigate the complexities of modern commerce, while leveraging machine learning to provide accurate demand forecasting, streamline purchase orders and optimise stock levels. This enables clients to avoid costly stock-outs and overstocking scenarios, freeing up time and resources to focus on growth and innovation.
Laura Kennedy, principal analyst at CB Insights, observes a significant trend in the latest wave of funded fashion retail tech startups: the central role of artificial intelligence, especially generative AI. Algo, a competitor out of Michigan, which raised $20 million in January, similarly employs an AI-powered platform equipping customers to intelligently plan, optimise and distribute their products globally. Emerging companies in this space are leveraging AI to create advanced virtual assistants that not only respond to user queries but also reveal critical insights. By doing so, they’re addressing a long-standing challenge in the industry: effectively managing and acting on vast amounts of information. “The data is all there, but we don’t know how to interrogate it,” Kennedy explains.
Meeting unique challenges
Demand planning in fashion is far more complex than in most other industries. It’s not just a matter of predicting how much shoppers will buy, companies must also predict what styles and trends will resonate in a constantly shifting landscape. Seasonality plays an outsized role, as new designs and silhouettes continuously emerge, while the sheer variety of choices available to consumers adds another layer of complexity. The breakdown of traditional demand patterns is also posing an unprecedented challenge to fashion brands, making accurate forecasting and demand planning more difficult than ever.
“Supply chains get disrupted, and seasonal factors and weather are much more variable than they used to be, and all of these things just mean it’s a much bigger problem for retailers,” says Neil Saunders, managing director of retail at Globaldata.
Broadly speaking, the problem with old-school planning and inventory software is that it allows users to react to crises, but lacks the tools to prevent them, says Bouhdadi. That headache was the genesis for his startup, the concept for which the co-founders began building during their tenure at McQueen. Frustrated with outdated systems, they developed a data-powered platform that not only streamlined operations, but played a crucial role in tripling the house’s revenue to over $800 million in just five years, according to Autone.
Now, the three-year-old startup is used by over 50 brands globally, including Stüssy and Zadig Voltaire. It empowers mid-market companies to make data-driven decisions that minimise waste and prevent overstock while ultimately boosting profitability. Autone will soon launch services for sporting goods and homewares, expanding beyond its current categories of fashion, beauty and accessories.
It’s little surprise that investment in fashion-focused demand forecasting and inventory management solutions peaked between 2021 and 2022, mirroring the overall trend in the venture capital market, according to analysis by CB Insights. Even with a tightening of venture capital this year, investor confidence in this sector remains robust, Kennedy says. The number of deals year-to-date is approaching the levels seen in 2021, indicating sustained interest despite smaller funding rounds and fewer deals overall. Companies that secured funding this year include Algo, Aptean, Blue Yonder, Hakio, Impact Analytics, Invent Analytics and o9 Solutions, in addition to Autone, per CB Insights.
Bouhdadi wants to bring the power of generative AI deeper into Autone, and hopes to forge an official partnership with big names like Open AI’s ChatGPT or Anthropic, the company behind Claude, a similar large language model and AI assistant. “We truly believe generative AI is the biggest revolution since the internet and the iPhone,” he says. “But meaningful things need to come out of that. Otherwise you’ll end up with just a gimmick.”
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