Fashion In The Time Of Artificial Intelligence
Have you ever had a thought and watched it pop up on your phone screen minutes later? If the answer is yes, you have been mapped. Michal Kosinski, a professor in Organizational Behaviour at Stanford University, studied 87 million Facebook users to create a mathematical profiling system that identifies people’s psychological traits from their internet activity. Although the research was meant to warn people of how their data could be misused, it laid the groundwork for what is common practice today. Each click is an insight into your brain, each ‘like’ providing fodder for a database used by brands, agencies and apps to track and manipulate your online behaviour. Everything from our likes and dislikes to our consumption habits becomes increasingly shaped by big data analtics.
Abdullah Abo Milhim, Postgraduate Programme Leader at Istituto Marangoni School of Fashion, was in the city to host a session on ‘The Fashion Value Chain in the Age of Big Data, Analytics & AI’ and how they are integrated into fashion business models and their implications on the emergence of new value chain strategies. He tells us what the fashion industry can learn from this.
What is Big Data Analytics (BDA) and why is it so important in fashion today?
Big Data refers to large volumes of structured and unstructured data that can be collected, stored and analysed simultaneously (in real time). Big Data can provide the fashion industry with insights that could lead to an in-depth understanding of consumer behaviour, and analysis of various variables on both sides of the supply chain. As the industry shifts increasingly towards personalisation, Big Data can provide fashion brands with new frontiers in areas such as trend forecasting, supply chain management, consumer behaviour and stock management.
How can Big Data create value?
We are seeing the fashion industry being disrupted by changing consumer behaviour. Through a deep understanding of trends and changes across the whole supply chain, Big Data Analytics can assist in devising new approaches in responding to changing consumer needs, lower costs and improve productive efficiency.
In what way is Big Data Analytics and Artificial Intelligence (AI) best suited to merge with existing businesses?
As data is collected from multiple sources, AI provides ample opportunities to understand behaviour through the various data sets. This allows brands to forecast and predict consumption patterns and trends in behaviour. Thanks to machine learning, data is now able to generate new tools for business analytics which can provide a better understanding of behavioural trends within a smart store environment and in the context of the relationships with vendors or suppliers
Luxury business giants have data analytics at their disposal for innovation. How does BDA affect small businesses?
BDA is also used by smaller business. It is a very important tool for them to capitalise on their ability to respond to any results or trends shown in their data sets. Although business giants have the ability to invest in sophisticated data platforms, smaller businesses can be in a stronger position to reshape their business models and value-chain strategies in a timely and structured manner.
How does big data analysis and AI assist in sustainability in fashion?
Data has the ability improve the quality of the information shared between different stakeholders. Suppliers are encouraged to be more responsible and aware while engaging in business transactions. AI, especially when combined with analytics, can assist brands in conducting an in-depth analysis of their cost structure, improve margins and reduce over-production waste. This provides brands with a better understanding of consumer behaviour, more accurate estimations of production levels, better inventory management, and efficient sourcing.
Luxury brands take pride in quality, the time spent making a specific piece with human labor, and intensive techniques. If AI is put to use at the production cycle level, does that change the way we look at luxury market too?
AI doesn’t mean anti-craftsmanship. Luxury can evolve with technological developments, and yet remain unique by preserving its DNA and history. Luxury brands are using AI to gain high-quality information on their customers. This could potentially allow them to create personalised products and customise their product offering online.
How is a BDA + AI model store different from traditional stores?
In smart store environments that are powered with AI and Analytics, there is a flow of real-time information that provides the brands with valuable information on conversion rates, heat maps, engagement with the store design, and a live monitoring of stock levels. This has advantages across the whole supply chain, specifically in areas around dealing with a shorter cloth range, and situations where the points of demand and supply are closer to each other.
What are five important points to keep in mind while altering a business model to data driven model?
Creating a culture around Digital Transformation.
- Understanding how the new business can create and sustain value.
- Preserving the DNA of the brand
- Ensuring that there is alignment with stakeholders’ values
- Ethics and integrity in the use of data.
Cognitive Prints, the AI tools developed by IBM for the fashion industry, will soon be capable of designing patterns on their own. But design is as much about historical crafts-weaves as technique, and these are governed by human instincts and emotions. How would AI interact with indigenous practices?
Nothing beats the human touch, regardless of how much technology develops. Cognitive Prints can provide designers with an added edge to trend forecasting. It’s interesting that AI plays a strong role in integrating together images, data sets, blogs, architecture and colours. Its benefits will be largely felt in areas of trend forecasting and predictive analytics around production and consumption.
How would BDA or AI interact with the market where there are pre-existing societal issues, body issues, gender differences, and racial differences?
The interaction between BDA and AI has implications for how we approach societal matters mainly in the context of understanding the views of various parties and their relation to one another, ex: consumers, media and pressure groups. Since such innovations provide companies with the tools to personalise their offerings, there is a possibility that racial and gender issues, for example, could be approached from individual aspects, and usually from social communities, with the latter changing concepts of marketing and ethical strategies in various industries.
Algorithms means dressing for the age of psychological mapping, does this mean it’s the end of creativity?
Although algorithms could potentially become able to replicate various design processes through machine learning, it is difficult to assume that creativity will die. Technology could replace some of the steps in the design process, but I don’t think design business models of unique and sophisticated brands can be replaced. The DNA of creativity will always be there, and technology is just an additional edge that can be considered, depending on the availability of competencies to capitalise on its benefits.
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