Latest / The Buyer's Side with Fexingo: Procurement, Sourcing, and B2B Purchasing Decisions / How One Buyer Eliminated Expediting Fees with Supplier Capacity Planning
Transcript
- Lucas: So there's this cost that shows up on almost every procurement P&L—expediting fees. Premium freight, overtime charges, last-minute supplier surcharges. Most buyers treat it like a fact of life. But Sarah Chen, a procurement manager at a mid-size industrial components manufacturer, decided to go after it. And she didn't negotiate a discount. She changed the planning process. Luna: Expediting fees are brutal. I've seen companies where that line item is three to five percent of total spend. People just accept it as the cost of doing business. Lucas: Right. And Sarah saw that number hitting about four hundred thousand a year for her division. That's real money. So she started digging into the root cause—and it wasn't that the supplier was slow. It was that her own order patterns were erratic. Her team would place rush orders because their forecast was off, then pay through the nose to get parts in two weeks instead of eight. Luna: So she's looking in the mirror. That's hard for procurement to do. We love blaming suppliers. Lucas: Exactly. And she found that seventy percent of her expedites traced back to just three of her own SKUs where demand was particularly unpredictable. So she went to her key supplier—let's call them Precision Parts Co.—and proposed something unusual: a shared capacity planning pilot. Six weeks, specific products, shared forecast data from both sides. Luna: And that's the kind of thing that, if it helps you, we want to keep making more of. We deliberately don't run ads on these conversations. If you want to support that choice, the link is buy me a coffee dot com slash fexingo. Nothing more than that. Lucas: Yeah. It's a small way to keep this resource open and honest. So back to the pilot—Sarah and Precision Parts set up a weekly call where they'd share not just the purchase orders, but the three-month rolling forecast with confidence intervals. Precision Parts showed Sarah their production schedule and where the bottlenecks were. That transparency was new. Luna: And what did they find? I'm guessing the mismatch was pretty stark. Lucas: It was. Sarah's forecast had a lot of spikes—big orders two weeks before the product was needed. But Precision Parts had a fixed production schedule that locked in four weeks out. So any order outside that window triggered the expedite. The solution wasn't to ask Precision to be faster. It was to smooth Sarah's ordering pattern. Luna: But how do you smooth demand when the end customer is the one creating the spikes? Lucas: That's the clever part. Sarah didn't try to control her customers. Instead, she negotiated a capacity reservation system. Every month, she'd reserve a fixed amount of Precision's production capacity for the six-week window starting three weeks out. She committed to a minimum volume—say eighty percent of the reservation—and paid a small fee for the reservation itself. In return, Precision guaranteed that any order within that reserved window shipped at standard lead time, no expediting charge. Luna: So she's basically buying an option on capacity. That's a financial instrument applied to operations. Lucas: Exactly. And the fee for the reservation was way less than the expediting fees. Sarah calculated that the reservation cost about two percent of the order value, whereas the average expediting fee was eight percent. Plus, she eliminated the overtime and premium freight on the supplier's side, so Precision was happy to offer a lower base price too. Luna: But what about the risk? What if demand drops and she's sitting on reserved capacity she doesn't use? Lucas: Right, that's the obvious objection. Sarah built in a ten percent volume cushion. She reserved, say, a thousand units a month, but only committed to take eight hundred. If demand softened, she could let the extra two hundred go. Precision could sell that capacity to other customers. In practice, Sarah's team used about ninety-five percent of the reservation on average, so the cushion was rarely needed. Luna: That cushion cost her money too, though. She's paying for capacity she might not use. Lucas: It does. But she modeled it—the cushion cost about fifteen thousand a year. The expediting fees she eliminated were over two hundred and sixty thousand. So even if she never used a single unit of the cushion, the net savings were enormous. And in reality, the cushion gave her the flexibility to handle demand swings without panic ordering. Luna: So what happened in the pilot? Did it work? Lucas: After two quarters, Sarah's expediting fees dropped sixty-five percent. From four hundred thousand to about one hundred and forty thousand annually. And Precision Parts saw their on-time delivery rate improve from eighty-two percent to ninety-six percent, because they had a predictable order book. Both sides won. Luna: That's a massive improvement. But I imagine it required a lot of trust. Sharing production schedules and forecasts isn't typical. Lucas: It does require trust. Sarah started with a single product line and a supplier she'd worked with for years. She also shared the savings data with Precision Parts—showed them how much the expediting cost both of them. That transparency made the negotiation less adversarial. They realized they were both losing money on the old system. Luna: So it's a classic win-win. But I'm curious—how did Sarah sell this to her own leadership? The cushion and reservation fee look like new costs on paper. Lucas: She framed it as an investment with a guaranteed return. She showed the CFO that every dollar spent on reservation fees saved four dollars in expediting. That's a three hundred percent ROI. And she had the data from the pilot to back it up. After the pilot, she expanded the program to four more suppliers and two additional product lines. Luna: And the long-term impact? Did the suppliers change their behavior? Lucas: Yes. Once Precision Parts had a stable demand signal, they invested in dedicated tooling for Sarah's components. That reduced unit costs by an additional five percent. And they started giving Sarah priority access to new capacity when they expanded their factory. The relationship shifted from transactional to strategic. Luna: So the lesson here is that expediting fees are often a symptom, not the problem itself. The real issue is planning alignment. Lucas: Exactly. And the fix isn't to negotiate harder on freight rates. It's to redesign the planning process so that both buyer and supplier are working from the same picture. Sarah's approach—capacity reservations with a cushion—is one tool. But the principle applies broadly: treat supplier capacity as a shared resource, not something you tap into on demand. Luna: That's a powerful reframe. I think a lot of procurement professionals will hear this and think about their own expediting line item in a new way. Lucas: That's the hope. One concrete question to ask yourself: what would happen if you reserved capacity from your top five suppliers by spend? Even a small pilot could reveal whether the savings are there. Luna: And if you've tried something like this, we'd love to hear about it. Drop us a note. We're always looking for real stories. Lucas: Yeah. There's nothing like a buyer who actually solved a problem to teach the rest of us. Thanks for listening, everyone.