How AI is Helping Minimize Waste in the Clothing Industry

Pawan Gupta explains the need of leveraging artificial intelligence to reduce wastage

Artificial Intelligence is a phrase that has been around for many years now. It started as fiction in movies and popular literature and steadily became a trendy word to describe intelligent machines. But today it's becoming indispensable, crossing over from fiction to fact, across industries.

The pandemic had a lot to do with this rising popularity and usefulness. At least 40% of active fashion consumers today are already availing of online services even as you read these words, increasing opportunities for deploying AI and deriving benefits. Without mistake, it can be said that we are in the midst of the fourth industrial revolution, where brands are gearing up to embrace the benefits of Artificial Intelligence and other new-age technologies.

Artificial Intelligence is used in different ways in the fashion industry. The industry is faced with several challenges, sustainability being the top on the list. But considering how widespread and popular fast-fashion trends are, change is a long-term endeavor. However, with the help of Artificial Intelligence, accurate predictions of trends, understanding customer preferences, managing workflows, and efficient supply chain are now reducing overproduction and minimizing wastage.

Tackling overproduction and overstocking has become a necessary concern among producers globally. United Nations estimated that the global fashion industry losing at least $500 billion annually due to a lack of and widespread use of recycling practices. Improper clothing disposal is also adding much to the loss.

How can AI help with the problems of overproduction and overstocking?

Overproduction of overstocking is common among producers, especially due to a lack of Data Intelligence tools. The balance sheet of demand and supply is often off balance because proper assessment of trends and demands is either not done or is not done accurately or efficiently. To identify a few factors which create surplus stocks:

• Inaccurate trend forecasting
• Lack of promotional activities
• Fear of understocking
• Dependence on historical data

The answer to the above challenges can well be found in the use of Artificial Intelligence. AI tools help in market research and fetch real-time information. The data gathered can be aptly assimilated into a real-time prediction system, in which case inventory management can become both manageable and sans waste. The data collected and stored can also be used for future references.

Customer behaviour prediction is another important contribution of AI to combat waste in the clothing industry. Customer behaviour is always changing, and one can never rely on any one-time data when it comes to this. Hence AI can be integrated into the retailers planning policy as the data analyzed can be used to adapt to the latest demand patterns.

Demand patterns can be predicted with the help of algorithms. It can even start on any social media platform. The algorithm gives accurate data about the market and hence can drive the retailers to make the correct decisions about how much to produce. This is what we now call smart demand forecasting or smart demand prediction. Customers' purchasing history can also be traced with the help of AI and can help the retailers to cater exactly to their demands. This may lead to lesser returns and help the customers make the right decisions.

Artificial Intelligence has become a part of the fashion industry in a way no one had previously predicted. We are denizens of a virtual world now and AI tools are constantly transforming the way we are manufacturing and marketing the products. Future predictions about robots being used for cutting and sewing are already in place. With the use of AI and new-age technologies, we can expect a reduction in wastage by about 60 to 70% as the processes will be automated with the highest possible accuracy.

Author:

Pawan Gupta, CEO & Co-founder at Fashinza