Latest / The Operations Podcast with Fexingo: Process, People, and Profit in Modern Business / How Puma Streamlined Its Global Supply Chain
Transcript
- Lucas: In 2018, Puma missed its revenue target by twelve percent. That's nearly half a billion dollars in lost sales — not because demand wasn't there, but because their supply chain couldn't deliver the right shoes to the right stores. Luna: Ouch. So they had the demand but couldn't physically get product onto shelves? Lucas: Exactly. And the problem was structural. Puma was running regional supply chains — Europe, Americas, Asia — each ordering independently, each with its own forecasting model. They were essentially three different companies sharing a logo. Luna: That sounds like a recipe for either overstock or stockouts. Which was it? Lucas: Both, actually. In some regions they had warehouses full of unsold sneakers, while in others they were air-freighting product at huge cost just to fill gaps. Their inventory turnover was awful. And the worst part? They were using eighteen-month-old data to plan production. Luna: Eighteen months? In fashion, that's practically ancient history. Lucas: Right. By the time a trend prediction made it through their planning cycle, the trend was already over. So they brought in an outsider — a guy named Bjørn Gulden, who came from the automotive industry, not sportswear. And he made a decision that seemed risky at the time. Luna: What was the move? Lucas: He centralized everything. Created a global supply chain organization called GOAL — Global Operations and Logistics. And he gave it authority over all regional planning. No more local fiefdoms. Luna: I can imagine that didn't go over well with the regional VPs. Lucas: It didn't. But Gulden's argument was simple: you can't optimize the whole system if every region is optimizing only for itself. And he had data to back it up. They found that regional forecasts were consistently wrong by about thirty percent. A centralized model, using the same data globally, cut that error in half within two years. Luna: That's a huge improvement. What else changed? Lucas: They shortened the planning cycle. Instead of one annual forecast, they moved to monthly rolling forecasts. And they invested in AI — not the flashy kind, but a practical demand-sensing tool that pulled real-time sales data from retailers and adjusted production plans every week. Luna: So instead of predicting what people would want eighteen months out, they were reacting to what was actually selling. Lucas: Exactly. Lead times went from eighteen months down to nine. And they cut inventory by thirty percent while maintaining a ninety-seven percent in-stock rate. That's a best-in-class metric in apparel. Luna: If today was actually useful to you, the way these stay ad-free is listener support — buy me a coffee dot com slash fexingo. Lucas: And it's listeners like you who make that possible. So if you've gotten something out of this, consider tossing a coffee our way. Luna: Yeah, it genuinely helps us keep digging into these case studies. Now, back to Puma — one thing I found interesting was the cultural shift. How did they get regional teams to buy in? Lucas: They didn't force it. Gulden actually created a system where regions could opt in to the centralized model and prove its value. The first region to adopt it was Latin America, because they were struggling the most. Within a year, their inventory turns improved by forty percent. Luna: So success bred adoption. Classic. Lucas: Right. Once the other regions saw those numbers, they wanted in. By 2022, all regions were on the GOAL platform. And the results were dramatic. Puma's gross margin improved by two hundred basis points, and their operating margin hit double digits for the first time in years. Luna: Two hundred basis points is huge in retail. Was AI the main driver, or was it the organizational change? Lucas: It was the combination. The AI tools gave them better data, but the centralization was what allowed them to act on it. Before, even if one region had perfect data, they couldn't share inventory with another region — each was managed separately. Now, if a sneaker is overstocked in Europe and understocked in Asia, they can reroute it in days instead of months. Luna: That's the kind of agility that makes a supply chain resilient. What about the production side? Puma outsources most of its manufacturing, right? Lucas: They do. About ninety-five percent of their products are made by third-party suppliers, mostly in Vietnam and Indonesia. So the challenge was getting those factories to respond faster. They implemented a shared forecasting system with their top suppliers, giving them visibility into demand twelve weeks out instead of six months. Luna: That must have required a lot of trust — sharing sales projections with suppliers. Lucas: It did. But Puma realized that if suppliers could plan their own production more accurately, everyone benefited. They even helped some suppliers install their own demand-sensing software. The result was that order fulfillment accuracy went from eighty-two percent to ninety-six percent. That's fewer rush orders, less air freight, lower costs. Luna: So it's a win-win. I'm curious — how does this compare to what competitors like Adidas or Nike are doing? Lucas: Adidas has been going through its own supply chain overhaul, but from a different starting point. They had a bigger e-commerce operation, so they were more focused on direct to consumer fulfillment. Nike's been investing heavily in automation at distribution centers. Puma's advantage was that they started from a lower base — they had more room for improvement. Luna: What about the human element? Did they lay off a lot of regional planners? Lucas: They actually retrained most of them. The regional planners became global category planners, focusing on product types — running shoes, lifestyle sneakers, apparel — rather than regions. So the headcount stayed roughly the same, but the work became more analytical and less siloed. Luna: That's a smart retention strategy. Losing all that institutional knowledge would have been painful. Lucas: Exactly. And the employees themselves said the new roles were more interesting. They were no longer just placing orders — they were analyzing trends, optimizing inventory across markets, and collaborating with colleagues in other regions. The turnover rate in supply chain actually dropped. Luna: I want to know about a specific failure. Was there a product launch that tested this new system? Lucas: Yes, the launch of the Puma Suede XL in 2022. That was a relaunch of a classic silhouette, and they had to coordinate a global drop across forty markets. Under the old system, each region would have ordered based on its own forecast, and some would have over-ordered while others under-ordered. Luna: How did the new system handle it? Lucas: They used the centralized demand-sensing model to allocate inventory dynamically. The initial production run was smaller than they would have done before — only sixty percent of total expected demand. Then, based on real-time sell-through data in the first two weeks, they adjusted production for the second batch. Luna: So they were essentially using a lean startup approach for a sneaker launch. Lucas: Exactly. And it worked. The first batch sold out in most markets, and the second batch was sized perfectly. They avoided both stockouts and heavy discounting. The sell-through rate at full price was eighty-five percent, compared to sixty percent for previous launches. Luna: That's a huge improvement. What's the biggest lesson other companies can take from Puma's transformation? Lucas: I think it's that supply chain isn't just a cost center — it can be a competitive advantage if you treat it as a strategic function. Puma didn't just buy better software. They changed the org structure, the planning cadence, the supplier relationships, and the culture. All of it together. Luna: And they did it without disrupting the business. That's the hard part. Lucas: Right. They phased the changes over three years, starting with the region that needed it most. By the time the full system was in place, they had proven the value at every step. That's a blueprint for any company facing similar challenges. Luna: It makes you wonder what other industries could apply this model. Maybe fast food or electronics? Lucas: Absolutely. Any business where demand is volatile and supply chains are global could benefit. The principles are the same: centralize planning, shorten cycles, use real-time data, and build trust with suppliers. Puma's case proves it works. Luna: Alright, I'm convinced. Next time I see a Puma store, I'll appreciate the supply chain behind those sneakers. Lucas: Same here. And maybe we'll do a follow-up in a year or two to see if they've sustained the gains. Thanks for listening.