Sustainable fashion? It’s possible with “predictive analysis”
Evo, a company based in Turin and London and created in 2013 out of the insight of Fabrizio Fantini, combines artificial intelligence and human intuition to support and direct companies’ choices by transforming data into indicators that predict market trends and create a positive cycle of growth for companies. This prevents the waste of money and inventory.
Turin, February 16, 2020
by Chiara Priante
When fashion harmonises with sustainability. The catwalks of Milan Fashion Week have confirmed it: even the most creative and visionary fashion houses today want to be green. They’re just like their customers, who are starting to become increasingly aware of the clothes they buy and are wondering where clothes come from and how they are made. But being virtuous actually starts much earlier in the process: in warehouse management. Turin and London-based Evo, a leading company in predictive analysis in the fashion world, knows this well. This start-up was created in 2013 out of the brilliant insight of forty-year-old Fabrizio Fantini who studied at Harvard and had years of experience in McKinsey alongside managers from all over the world. Evo has now become a heavyweight by combining artificial intelligence and human insight to support and optimise choice.
This vital synergy helps retailers sell the right products and, in turn, eliminate waste by anticipating market trends up to eight weeks in advance. This is how Evo has become a resource for what’s considered “predictive analytics”: optimising the provisioning of products in stores and setting prices by analysing historical performance, real-time data and demand forecasts. “Some studies have shown that most of the waste in the fashion supply chain is generated through retail”, explains Fantini. “Not only do inappropriate prices cause this waste but also the method and distribution of goods between stores and warehouses.”
With $100 billion in transactions “digested” by the system in the first six years of its life, Evo makes it possible to reduce leftovers in warehouses by 20 to 30 percent (and in some cases even over 40 percent), by creating a positive cycle of growth for companies and preventing waste of money and goods in stock. Among the merits of this alliance between machine and man: Evo counts on its team of young data scientists, a high percentage of whom are women. The Harvard Business School has even published a case study on the collaboration between Evo and Miroglio, a leading Italian company in the fashion and textile sector, as Evo was among the first to attempt to solve the problem of volatile demand in the fashion sector.
“In 2013, I finally united all the arguments in my PhD thesis at Harvard, which essentially showed how the use of intelligent algorithms could help a company make better predictions and thus more targeted decisions”, says Fantini. He was just 34 then (older than the average age of his current data scientists, however). Since then, the company has established various international academic collaborations. Its strength lies in giving concrete solutions to problems related to warehouse management, inventory and promotions, in establishing ideal sales prices, and in combining statistics with so-called “advanced machine learning” and human intuition.
In practice, Evo transforms data into indicators that predict market trends and uses that data to help companies make decisions. In fact, so many variables influence demand: historical sales, geographical area and climate are all used to predict potential demand and, as such, to optimise prices, promotions and inventory and to plan every detail.
But it doesn’t stop with fashion. Evo is now tackling a new challenge in large-scale organised distribution with a new and ambitious goal: preventing food waste.
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