JD Sports has come a long way from its roots as a single shop in the Greater Manchester town of Bury.
Forty-five years on, JD Group is a £13 billion revenue global retailer of sports, fashion and outdoor brands. Having made more than a dozen major acquisitions over the years, it now has more than 4,800 stores across 51 countries, alongside multiple online channels.
After embracing AI platforms to connect more potential customers with its products, it is also looking to harness the emerging technology to improve processes – including in its supply chain.
Matt Lemon, JD’s head of supply chain technology, has this year taken part in an agentic AI pilot programme run by unified commerce and supply chain software company Manhattan Associates alongside the likes of L’Oréal.
Lemon took part in a panel discussion at the recent Manhattan Exchange conference in Milan alongside Raphaël Herve, senior director – technical & support services at Manhattan Associates; CEVA Logistics IT director Johan Berghs; and Antoine Prat, fulfillment process global director at L’Oréal.
He explained to BusinessCloud afterwards how agentic AI is ‘unpicking legacy constraints’.
“What we’re doing is lifting away from the legacy systems that we’ve inherited over the years, either through acquisition or through development of our own business at speed,” he says.
“When you see the rapid growth of JD over the past 15-20 years, we’ve not really had that opportunity to just stop and assess, then rebuild for the correct technological future.
“So a lot of the work that I’ve been trying to do in my four years with JD is to unpick some of the legacy constraints we have – and tools like agentic AI really help me to do that.”
One example of an operational AI agent deployed by JD is a ‘wave coordinator’ which manages and schedules the release of order batches – called ‘waves’ – to the warehouse floor.
“The wave coordinator is there to effectively analyse our workload, our order profile, and then create the wave strategies to optimise the flow through the warehouse,” explains Lemon.
“Thinking of it from the point of view of a control room manager, we ask: what would I need to make my processes faster? And for me, it’s to remove that decision-making which could take multiple hours [for a human to perform].
“How do we sequence our distribution across Europe: to France, to Spain, to Italy, to Sweden, to wherever we want to ship to? Let’s just not think about it anymore – let’s have an agent do that for us.
“We’ve seen a really strong use case in that area in the past few weeks.”
Manhattan Associates CEO Eric Clark told its 10th annual EMEA customer and partner gathering that “complexity in your software is a tax”. His chosen metaphor was an airliner cockpit which once upon a time required five crew, but now needs two as the instruments absorb that complexity.
In AI-enabled warehouse terms, its software now claims to make deployments up to 50% faster, while stores and orders can go live in as little as 100 days – a rapid improvement on a year ago.
Lemon says one of the major operational benefits of its AI agents is “getting back time to make decisions elsewhere”.
“The tech-focused agents are allowing us to free up the real skilled people that understand our business and core systems to focus on something else – instead of responding to a data issue on the end of a ticket or a routine and repetitive incident that arises in a facility,” he continues.
“So what we’re really doing is just shifting the focus of people – that’s where we’re finding the value.”