In spite of the fact that we typically conceive of fashion as an intuitive activity, it has historically demanded a significant amount of information and understanding. All of the data, from the trickle-down and bubble-up of fashion trends to market statistics and the sizing details of clients, needs to be processed in an ethical and fair manner in order to adhere to issues surrounding privacy.
In this process, what exactly does the role of the designer entail? How should we deal with this information such that it may also be used for creative purposes, in addition to marketing and sales? Are there any opportunities for co-creation that involve the use of data, or for the utilisation of this technology to engage with the real-time input of customers? For the fashion designer, does data present a friend or a foe?
In order to get answers to these and other questions on the use of data in the fashion industry, both by fashion designers and by the fashion system as a whole, in order to optimise and streamline the fashion supply chain, we asked an expert panel to answer these questions.
Have faith in both your gut intuition and the numbers.
Julie Pont, Fashion & Creative Director of Heuritech, claimed that “you can say my gut feeling is backed-up by very early signals data.” “You can say my gut feeling is backed-up by very early signals data.” The Artificial Intelligence (AI)-driven solution that the Paris-based business offers is a trend predicting tool for the fashion and luxury industries. Heuritech employs machine learning algorithms to sift through millions of social media photographs. With the assistance of their fashion team, they examine early trend signals and assess how they are performing in various regions.
Pont, who has a background in fashion design and is traditionally schooled in the industry, remarked that it was initially difficult to trust data. “To tell you the truth, because I come from a creative family, I was a little bit anxious. Would this be able to replace my current job? I felt overwhelmed by the potential for more value that could be added by data. I was going with my instincts, which is common practise in the fashion industry. You are a designer, thus you are well aware that your natural instincts and creative abilities are the primary reasons for your employment. However, I quickly came to the conclusion that data is not meant to take the position of designers but rather to assist with the uncertainties “admonishes the French fashion designer based in Paris.
The company Pont views data as a way for fashion designers to save time. “As a creative person, you have access to a wide variety of resources that can serve as sources of inspiration; nevertheless, you are faced with an overwhelming amount of demand from the market, the brand, and the customers. Technologies such as AI-powered trend research have the potential to improve the efficiency and quality of the designer’s research process while also reducing the amount of time spent on it. As a fashion designer, I find that relying on statistics helps me make more confident creative choices. It substantiates my arguments, as Pont puts it.
The examination of data, as well as customer behaviour
If, when viewed from the standpoint of the designer, data can assist in making better judgments, when viewed from the standpoint of the consumer, this is not necessarily the case. According to Jonathan Chippindale, Founder and CEO of Holition, a creative technology agency in London that creates immersive experiences for retail, the key to correctly analysing data is to look at consumer behaviour and recognise that it is always subject to change. Holition creates these experiences for retailers.
“The concept of algorithms carries with it a significant air of irony. We have access to an endless amount of knowledge and data, but algorithms are sorting it into categories that they believe will be of greater interest to us, while simultaneously deleting categories that they believe will be of less interest to us. In some respects, it is driving us toward the middle of the bell curve, which is the point at which, if you take all of the colours and mix them together, you end up with grey. It’s the same as the average. But that doesn’t seem very human, does it? That is not how we do things around here. Everyone here has their own unique style. We are going to change our behaviour. Our conversation will take a new turn. Different things appeal to each of us, “says Chippindale.
And he continues: “It would be intriguing to me if we could identify the origin of feelings and behaviours, as well as the factors that contribute to those behaviours, and then incorporate all of that information into the analysis. Recognize both a tendency to experiment and a tendency to uncover new information. I’ve heard that the view from the peak of that mountain is spectacular, and I want to see it for myself. There has never been anyone else there before, but I’m going to go there anyway.’ This is the essence of what digital media entails.”
According to Chippindale, the most significant impact that digital technology is having on the fashion business today is having on the relationship that brands have with their customers “The brands have been forced to relinquish their power. When I worked in marketing, I used to tell women what to wear, how to wear it, and when to wear it. Brands also used to dictate when women should wear what they sold. Someone directing you what to dress just feels like the wrong thing to do in this day and age; that behaviour just looks crude.”
Does having more data result in better products?
How can companies position themselves when they have access to consumer data and can influence purchasing decisions if it feels bad to advise the consumer what to wear? The issue here is one of consent, and if I as a customer am willing to give a company permission to collect my data and work on improving the things that are available to me, then I am the one in charge.
But how exactly can a business get feasible and scalable consumer consent in relation to data collection? An on-demand system is the solution, according to Beth Esponnette, Co-Founder, Chief of Product, and Executive Chairman of Unspun, a robotics and digital apparel company that builds custom-made jeans. Unspun builds pants based on the customer’s specific measurements. “The more data and knowledge you are able to obtain on that individual, the more deliberate the product will be.” Unspun relies heavily on this idea, as Esponnette explains further: “We are making an effort to reverse the process by beginning with the consumer and working backwards to develop a solution that meets their needs. Following the customer’s body scan and selection of the desired design, we will subsequently manufacture the device on the customer’s behalf.”
And is it always the case that the customer has a clear idea of what they want? “That is something that needs to be sorted through,” Esponnette says. “If people tell us, “No, I like to wear my pants like this,” they might not always know exactly how, but this is information that we have gathered over the course of time and incorporated into our algorithms. However, this raises two questions: do we have a biassed workplace? Is there a possibility of prejudice because of the way in which we’ve classed people? “asks Esponnette. Because the issue becomes more complicated as more research is done on how data might affect the fashion system, it is even more vital that we know with whom we are sharing our data. [Case in point:] [Case in point:] [Case in point:] [Ca
Data can be utilised by fashion designers to gain a better understanding of their clientele, to assist them in the creative process, to assist them in making more informed judgments based on current trends, and/or to assist them in selecting an alternative aesthetic option. If we respect data and the sources from which it comes, the options are practically limitless. Our actions as customers, both online and off, generate data that can be used in various ways. Everything we do, every day, generates data that can either be used to our advantage or to our disadvantage. The challenge is to put it to good use and to distribute it evenly. As an additional point, Jonathan Chippindale made at the conclusion of his interview, “The algorithm is not an oracle; rather, it is us human beings who ought to be asking questions.