Decathlon is one of the world’s largest sporting goods retailers, with operations in over 60 countries and turnover of more than EUR 11 billion each year.
China is the French company’s second-largest market in terms of stores, with over 300 outlets spanning 100 major cities, offering equipment and clothing suitable for more than 80 sports.
While many overseas sports retailers have found it difficult to carve out a niche in China, Decathlon has thrived due to a knack for embracing the rapid changes that continually disrupt the domestic retail market.
For example, Decathlon China adapted to the drop-off in footfall at its brick-and-mortar stores during the COVID-19 pandemic by investing in a business-to-consumer (B2C) ecommerce warehouse solution to improve the efficiency of its supply chain.
Looking ahead, an in-country industrial value chain that manufactures more than 90 percent of the goods Decathlon sells in China offers unique scope to employ artificial intelligence (AI) and advanced analytics to enhance customer experience and operational efficiency.
McKinsey Senior Partner Alex Sawaya spoke with Decathlon China CEO Marc Zielinski about how AI and advanced analytics are transforming Decathlon’s performance in China.
Their conversation covers Chinese customers’ expectations for on-demand order fulfilment, leveraging data to improve customer engagement throughout their sporting journey, and pioneering customer-to-manufacturer (C2M) models that rely on data-driven factories to deliver personalized products.
McKinsey: How are AI and advanced analytics shaping the future in China?
Marc Zielinski: China is an amazing test ground for AI and advanced analytics, and use cases will continue to grow from both a retail and industrial perspective. Vast amounts of user data, supported by a vibrant mobile payments and ecommerce ecosystem, will drive an expansion of retail use cases.
At Decathlon, we believe the use of data will revolutionize the entire traditional value chain.
A great example is the way we are working with Geek+, a Beijing-based company that specializes in autonomous mobile robots, to explore new robotics and software technologies in the supply chain. We are collaborating with them to create a more sustainable future for the sports retail industry.
Marc Zielinski biography
Leads Decathlon China as CEO, overseeing the company’s largest store network outside France, and driving a new omnichannel strategy that focuses on encouraging Chinese consumers, particularly young families, sports enthusiasts and women, to embrace the communal benefits of sport.
Served as Decathlon Hong Kong CEO from 2016 to 2020, where he launched the company’s first brick and mortar stores in the city, and developed a successful China-wide ecommerce platform.
Directed the group company’s global omnichannel and digital transformation strategy from 2015 onward, helping grow global revenue by 9 percent in 2019 to $13.4bn, supported by a rebound in sales in France, Decathlon’s home market.
Held various executive positions at Decathlon France from 2006 to 2020, including Europe Retail Chief Financial Officer and Retail Group CFO, International Services Director.
Advanced from Italy CFO Retail & Production to become Asia CFO, Decathlon Production in the decade to 2003, before moving on to act as China CFO, Services Director until 2006.
McKinsey: Where do you see the biggest application opportunities for AI and advanced analytics in retail in China?
Zielinski: We will focus on improving our understanding of customers, and that will drive new AI and advanced analytics use cases and opportunities along the whole value chain, from product design, through to manufacturing, logistics, and retail. The purpose is to more efficiently deliver our value proposition.
In China, our customers increasingly want their dream product now, on-demand. That means that we have to adapt the whole value chain in order to be there wherever and whenever the customer needs us.
McKinsey: What differences do you see between China and the rest of the world in retail?
Zielinski: China is two years ahead of the curve. In marketing, the use of short videos and livestreaming, where the content is generated by Key Opinion Leaders and Key Opinion Consumers, is amazing. Interestingly, the omnichannel strategy is a little different from what we see in Europe. For example, private domain operations, in which retailers leverage customer databases to maintain long-term relationships, increase retention rates, and open more opportunities to sell over a customer’s lifecycle, are a very powerful tool for building communities in China, and will be a major part of our strategy going forward.
McKinsey: What are some of the key challenges you have encountered along Decathlon’s digital transformation journey in China?
Zielinski: We started the digital transformation at a global level years ago; we understood that we cannot be a follower – reacting to new business cases and trends as they emerge among competitors. In order to anticipate those trends, we have to rely on accurate data that feeds into AI and advanced analytics models. We also realized that retailers must become tech and data-driven companies.
The transformation goes beyond AI because it is led by people, so the challenges are connected to onboarding the right skills and capabilities. As a traditional retailer, we had to make trade-offs in the way we develop the business and become more digital, which in turn created secondary challenges around convincing our teammates of the need to change.
In China, we had to adapt locally and develop our own infrastructure, and we are accelerating that across technology, infrastructure, skills, and talent development. With that foundation in place, we can start developing new use cases, and the algorithms supporting those use cases.
McKinsey: You mentioned earlier that you intended to begin with a focus on your customers; how do you go about engaging them in China?
Zielinski: In China, we have a base of 25 million customers, of whom 14-15 million are active members. The key question is how to leverage our customer relationship management (CRM) database. Understanding the customer lifecycle is extremely important as it allows us to better serve customers while increasing cross- and up-selling opportunities.
For example, if a member buys a bicycle, we can anticipate when it may require maintenance. Or if you buy running shoes, we can predict that after you run 500 kilometers, it might be time to invite you to test a new pair. Spamming the member base with irrelevant content is no longer acceptable. People nowadays expect personalized content that is relevant or useful for the repair or maintenance of their products.
McKinsey: Can you give an example of a use case where AI and advanced analytics have made a major impact?
Zielinski: In China, data is increasingly impacting the creation of new product categories and product designs. We can no longer rely on instinct to anticipate trends. Partners such as e-commerce platforms provide us with great feedback and insight that we use to develop new categories or new products.
Meanwhile, the sports segment is rapidly changing. Until now, we would have said we are a mass market retailer, but in China, AI and advanced analytics are enabling mass customization. Their adoption is also driving the emergence of customer to manufacturer (C2M) market models, in which the customer can bypass logistics and distribution to purchase tailored products directly from the retailer.
The days when customers were prepared to wait days or weeks to receive personalized products are over. New types of factories, led by a AI and analytics, are acting as linchpins in data-informed value chains, that allow customers to receive personalized products within a very short turnaround time.
Another field is price optimization, which we have undertaken at a group level. In Europe, we are leveraging data to define price positioning with astounding results.