When sales of one of its leading brands began to mysteriously decline, Bestseller India needed to find out why. For answers, the company used a development model infused with data and AI to deliver products matching consumer preferences.
Using the agile IBM Garage Methodology, Bestseller India created Fabric.ai, the Indian fashion industry’s first AI-powered platform designed to help forecast sales potential and achieve better sell-through rates.
First AI-powered fashion planning and forecasting tooldeveloped in India for the Indian apparel market
Cuts economic and environmental costsby reducing the amount of unsold inventory
Increases profitabilitywith higher margins and better sell-through rates
Business challenge story
Solving a mystery in the marketplace
When Denmark-based clothing retailer Bestseller opened its first stores in India 11 years ago, sales took off almost immediately. As a leader in the fast-and-affordable fashion industry, Bestseller excelled at designing trendy clothes and bringing new merchandise to market quickly. Bestseller India soon became India’s fastest growing fashion retailer. Revenues typically grew at annual rates of 50% as customers cleared the racks of popular Bestseller brands such as Jack & Jones, Only, Selected and Vero Moda.
But in 2019, something mysterious happened to the Only brand, a clothing label popular with the younger market. Until then, it was Bestseller India’s leading product line. “Only had suddenly gone down and there was nothing that we could figure out in terms of what went wrong,” says Ranjan Sharma, Bestseller India’s CIO and Head of Supply Chain. “We were puzzled and had to find out why it was going down.”
Bestseller India’s immediate focus was to turn around the Only brand. But while working on this specific business issue, management also recognized the opportunity to address a much larger, strategic issue facing the fashion industry — sustainability.
At the corporate level, Bestseller had launched a “Fashion FWD” initiative to bring sustainable fashion forward. In support of this worldwide effort, Bestseller India saw a high value opportunity to develop and digitize smarter design and planning tools that could minimize waste at the start of the creative process. By designing and producing apparel that more accurately reflects market demand, Bestseller India could go a long way toward reducing the high economic and environmental costs of unsold inventory.
On the way to consult with the IBM Research Laboratory in Bangalore, India, Sharma and his IT team had several key questions top-of-mind: “How do we optimize the designs we create rather than just going ahead and creating thousands of designs, and how do we optimize our inventory and sell-through rates? Could IBM help us solve these problems and bring in better insights from data?”
A smarter way to create and collaborate
After talking with several other prospective IT providers, Bestseller India chose IBM to help determine why sales of the Only brand had stalled and develop more powerful digital tools to support fashion design and preseason planning. “We needed a partner with a length and breadth of technology capabilities,” says Sharma. “But we also needed someone with domain knowledge. We found that the people at IBM had the best understanding of the fashion space.”
For its first IBM® Cognitive Enterprise innovation project with IBM Services®, Bestseller India set a very ambitious goal: to develop a totally new platform with AI capabilities to support decision-making related to preseason design, planning, production and forecasting. “This was a big change for us, for the planning teams to move from a gut-feeling to AI-delivered information that we wanted to implement,” says Sameer Ambalkar, Head of Business Solutions at Bestseller India.
The new application was deployed to the IBM Cloud® Kubernetes Service, a managed platform as a service (PaaS) offering that met Bestseller India’s requirements.
To support such a big change for its company and employees, Bestseller India wanted to collaborate with experts who could introduce innovative practices and new ways of working. So, the company chose to work with the IBM Garage — a proven framework that integrates people, processes and technology to transform business and culture. During the IBM Garage Enterprise Design Thinking™ Workshop, IBM and Bestseller India experts created a roadmap for co-creation, beginning with user research.
“Collaboration started right from the outset in terms of getting inputs from designers, merchandisers, buyers, brand heads and IT professionals — the team that would actually be using this tool,” says Zian Lakdawalla, Business Transformation Manager at Bestseller India. “There were personas created for designers and buyers, and all of these ideas led to the development of the project.”
The project focused on creating intelligent workflows for key business processes and using IBM Watson® AI tools to help predict the best products to incorporate into new offerings, determine the right product mix for each store and improve the efficiency of the supply chain. “IBM Garage is a fantastic model to work with,” says Sharma. “It cuts across technologies and domains to get a better solution and leverage what is ready.”
“When IBM said that we needed to bring technology into the design process, it was a big ‘aha’ moment,” says Mukta Srivastava, Only Brand Product Manager at Bestseller India. “Now, designers will spend more time on higher value work instead of managing files and data.”
The enormous size of the Indian economy and large differences between individual markets was a huge challenge for the development team, but a challenge that could be addressed within the IBM Garage framework. “We have a lot of demand that varies from one region to another and understanding that was very key for us,” says Lakdawalla. “We wanted to see how good the tool could be to predict better sell-through rates and see what is really trending to maximize our investment.”
After months of work and iteration, the Bestseller India-IBM Garage team brainstormed 61 unique concepts for the platform — eventually named Fabric.ai — which became India’s first AI-powered tool for the fashion industry.
AI-powered intelligent workflows
The first version of Fabric.ai included a comprehensive set of seven core AI modules, along with six specific tools for designers, buyers and merchandisers. Whether users accessed data from previous seasons or updated data for future use, Fabric.ai enabled immediate cognitive analyses of how well products are performing.
The user experience was further enhanced by an interface that displays sales and product information in an easy-to-use visual format. Per the original design brief, Fabric.ai initially focused on the Only line of apparel, but the platform has the scalability to handle Jack & Jones, Vero Moda and other brands in the future.
“The platform is well thought-through and robust in terms of understanding fashion, which helps bring in data in a more predictable and easier format for all users to engage in,” says Ambalkar. “The model has been the crux of this, and IBM helped make it possible.”
Designers appreciated the ability to use a visual similarity tool that compares new products with products from previous seasons. “Fabric.ai will help us pore through information that is relevant and in a pictorial form, which is much easier for designers to consume than looking at spreadsheets,” says Srivastava. “It will become much easier for them to deliver a product that is closer to customer demand and make historical performance information available at the click of a button.”
Fabric.ai also provided a better look at the sales performance of specific products at the retail store level. “The store-view option will help us find the right assortment for each store to help the buying and merchandising team,” says Lakdawalla. “In addition to helping predict which products will be successful in the next season, the tool will help us focus on the supply chain, prioritize the sell-through of current products and help ensure that inventory doesn’t pile up.”
Although the Fabric.ai project began with the IBM Garage team members working together at Bestseller India’s office location, the agile and user-focused IBM Garage Methodology also supports virtual development and collaboration. When Bestseller India employees began working remotely after the onset of the COVID-19 pandemic, the development of Fabric.ai software didn’t slow down. “We continue to provide the support that the team needs,” says Lakdawalla. “It will just build up as the days and months progress. To take this process forward, that is what I feel will be the biggest game-changer.”
With many stores closed because of the pandemic and large segments of the retail industry being put on hold, having the platform in place will provide a head start when normal business conditions resume. “At some point, we had to start using AI technology and leverage it to develop better performing product ranges,” says Srivastava. “With IBM, it has been a great journey and it is going to bring in a lot difference in how we’re delivering and how the ranges perform with our customers.”
“Given the current situation, this is not just a need but a must-have today,” says Sharma. “The shops and the warehouses are changing. How will we be able to create new business models which can solve current and future problems and reshape our business? These are issues we will continue to work on with IBM.”
About Bestseller India
Headquartered in Mumbai, Bestseller India (external link) operates 250 exclusive brand outlets and also sells its clothing brands through over 1,500 external multi-brand stores. With over 3,500 employees in India, the company is part of the parent Bestseller organization based in Denmark. Founded in 1975, Bestseller is a family-owned fashion company operating in 70 markets around the world through more than 2,800 chain stores and 12,000 external multi-brand stores. Bestseller has over 17,000 employees worldwide with annual revenues over EUR 3.5 billion.
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