Gucci is a great example of a fashion brand leveraging NFT to bring something new and unique to the market, let’s see how.
Some things never change about the fashion industry—like little black dresses never go out of style and Milan will always be a fashion hub— but there are some things in recent times that have consumers begging for change. Most notably, the harmful impact that the fashion industry has on the environment has made headlines that have forced shoppers to think twice about the companies they are buying from.
Companies have been troubleshooting how to decrease their carbon emissions, often by sourcing more sustainable raw materials, promoting upcycled clothing, or finding ways to utilize less detrimental transportation methods in their supply chain. It is not unusual for companies to promote environmentally friendly practices for the sake of looking good in the public eye, and either is not actually doing all they can for the environment or not doing anything at all and lying about their initiatives (this practice is referred to as greenwashing). Although these practices happen more than you would think, all hope is not lost for the fashion industry.
In recent years, the idea of an impact first business model has surfaced. An impact first business has a cause centered at the core of its operations, meaning that it is cause-oriented first, and profit-driven second. This might mean putting profitability opportunities on the back burner for the first few years of the company while resources are being dedicated to an initiative.
Following this business model is a new startup fashion brand, Finesse. Not only is Finesse helping to combat high carbon emission levels, but it is subsequently revolutionizing the fashion industry with its use of Artificial Intelligence technology.
Artificial intelligence can already be found used in online retailing to help customers locate an exact item to purchase from just a picture. However, how will AI affect the fashion industry in the long run?
Finesse is testing the boundaries of the industry by using artificial intelligence to not only predict trends with pinpoint accuracy, but to help reduce the amount of waste and carbon emissions in its supply chain.
Here is a sneak peek of the topics we will be discussing today:
Launched in 2021, Finesse is a fashion-focused tech startup founded by CEO Ramin Ahmari (he/him). The company was founded with two main goals in mind: cut back on production waste and produce clothes for individuals of the BIPOC and LGBTQ+ communities who feel underrepresented in the world of fashion.
Ahmari identifies as queer non-binary, and throughout his upbringing, in a small German town, he used fashion as a means to “navigate the intersections of his identities and deal with the associated labels” (MaC Venture Capital). As a teen, he attended a boarding school in England before pursuing a joint BS/MS in Computer Science with a concentration in Artificial Intelligence at Stanford. During this stage of his life, Ahmari held internship roles at financial firms such as Morgan Stanley and BlackRock.
It was at roles like these that Ahmari realized the impact that data has on predicting the future of entire industries. In an interview with Fortune, Ahmari explains, “we would look at all of this financial data and were able to make multimillion-dollar decisions…but we don’t look at social data in the same way, even though it’s quite expressive” (Fortune).
With data analysis at the core of the company’s operations, Finesse hopes to produce only clothes that it is sure consumers will want, based on numerical information generated by artificial intelligence, as well as input from shoppers on social media sires. Because of this, the brand expects to fall along the lines of “Netflix meets Zara”, in the sense that “Similar to Netflix, when you go [the] site, you see only the drops [they] know you’ll like. You’ll never sift through 50,000 articles of clothing to find the one you like” (Fortune).
Because of this extremely accurate forecasting method, Finesse hopes to limit the amount of clothing waste, due to the fact that excess clothes will not be produced. When a clothing item drops on the website, a
Traditionally, trend forecasts are made by designers and buyers who predict what consumers are going to like in each collection. Especially with luxury brands, there is a lot of time and effort placed in forecasting the demand for various merchandise. Luxury fashion companies produce about two-four times a year, in line with the seasons. Before each drop, luxury brands spend days and weeks researching the wants and needs of their target audience. To do so, they use trend forecasting software, focus groups, and social media to create new designs for the next season.
Fast fashion brands, which have gained popularity over the past decade or so, drop about 25 collections a year. The goal of these companies is to stay as on-trend as possible and to get products to their shoppers as quickly and efficiently as possible. To ensure that they produce clothes for the masses, fast fashion brands carry tens of thousands of SKUs at a time. To pump out this many items in a year means that a lot of forecasting is true guesswork, and merely “seeing what sticks” for consumers. Consequently, those items that don’t “stick” end up in landfills or waterways and cause more harm than necessary to the environment.
Although luxury brands do not use the same amount of guesswork and hoard the same amount of merchandise, high-end brands are still guilty of environmentally detrimental practices. Recently, heritage fashion house Burberry was under attack for setting fire to over $30 million worth of merchandise in order to maintain brand value and prevent the sale of stolen, secondhand merchandise at bargain prices. It was unethical practices such as these that inspired Ramin Ahmari to create Finesse and utilize new Artificial Intelligence technology to create a more sustainable fashion business model.
As we touched on earlier, the Finesse business model was crafted from the same principles used by the finance industry to predict stock performances. To create predictions like the one’s economists and hedge fund traders do but for the fashion industry, Finesse is using social media to collect data from consumers about future demand. The brand is using AI machine learning techniques, hand-in-hand with mathematical and statistical analysis in order to analyze fashion accounts on Instagram.
These artificial intelligence machines collect data from millions of comments across the profiles of models and influencers to track the emotions of targeted consumers. Through this data, Finesse is able to learn exactly what shoppers are looking for in clothes and catch trends right as they are gaining steam. Most of the items worn by influencers and models, however, are out of the price range of many shoppers. Finesse is able to understand the feelings towards trends and then sell them at a lower cost to appeal to its target market—no item that has been released so far had been priced higher than $116 (mainly due to the fact that since forecasted demand is fairly accurate, the brand can afford to list items at a lower price). Once the data is gathered and trends are identified, AI generates designs of merchandise that reference current trends, but are slightly different as to not create an exact copy of an item.
The next phase of the Finesse production process is a voting feature where consumers can pick the piece that they are most excited for in a new weekly drop. Featured on the Finesse website, the brand posts a few 3D rendered items for the consumers to pick between. Because of this technology, manufacturers at Finesse are able to know which item is favored, and based on the vote percentages, predict the demand of the item once it is released. Finesse is also taking advantage of a fast supply chain. The entire process of identifying a trend to having an item available for purchase in about 25 days in total. Even though Finesse is able to provide a short lead time for its unique products, it is unlikely that fast fashion brands will be able to replicate the trends because unlike Finesse (who utilizes solely 3D technology to draft prototypes), creating physical prototypes of these intricate designs would require many rounds of samples and alterations.
Not only are the production methods unique to the brand, but the products themselves are designed in an inclusive way that is not often celebrated in fashion yet. Each piece is designed to be gender-neutral, and also honors individuals of the BIPOC community in a way with “no reappropriation, just representation”, with a majority of the board and team being BIPOC themselves.
As its practices develop over the years, Finesse’s use of artificial intelligence will challenge the fashion industry to use the same lean business operations. Because consumers know that they are heard and feel cared about with a brand like Finesse, there is not much logic behind sticking with fast-fashion brands whose clothes are not made to last and are not manufactured in a sustainable way. Using 3D digital design uses fewer resources than traditional sampling methods and ensures that products can be in the hands of consumers in just 25 days, opposed to the traditional 5 months. This quick lead time ensures that trends do not go out of style before shoppers can have the chance to wear them. Since this is the case, consumers will not want to have to wait before they are able to purchase desired products (which are already to their exact specifications considering they were designed from their feedback. Shoppers are likely to choose purchasing options that have short lead times but are also sustainable, versus brands that are quick and not sustainable or have long lead times that are more sustainable (and more expensive).
Another way Finesse is likely to revolutionize the fashion industry is because of the fact that while the clothes are primarily designed through AI, the board and team running the company are from the target market themselves that they are trying to sell to. Many of the employees identify with the LGBTQ+ and BIPOC communities and are able to represent these communities with honor as opposed to the “white, older, cisgender men” that traditionally dictate the fashion industry.
While the fashion industry is notably one of the largest polluting industries in the world (second to only the oil industry), there are brands that are committed to change traditional, wasteful production methods. These brands often follow business models referred to as “impact first”, where the company is cause-oriented first and profit-driven second. One of the brands that operate under this principle is a new tech startup called Finesse. Founded by Ramin Ahmari, Finesse uses artificial intelligence machines to collect data from social media sites in order to accurately forecast fashion trends. These trends are into a 3D rendered object and are posted three at a time on the Finesse site for shoppers to vote for their favorite. Once the votes are in, the most popular item is released in one of their weekly drops, one at a time. And, because of the data behind the votes, the brand is able to accurately predict the demand of the product, which allows the company to charge less for the items and manufacture them with less waste. This differs from traditional production methods, in which companies spend months to produce a collection with hundreds of items, twice a year—or worse, following a fast fashion model where countless items are released twice a month. Finesse not only has sustainable practices at the core of its operations but inclusivity as well. All products are made to be gender-neutral, and the company produces clothes that represent individuals of the BIPOC community.
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