Latest / The Buyer's Side with Fexingo: Procurement, Sourcing, and B2B Purchasing Decisions / How One Buyer Cut Costs with Demand Forecasting
Transcript
- Lucas: So Luna, I want to talk about a procurement case that involved zero flashy technology — no AI, no blockchain, just a buyer who looked at a spreadsheet differently and cut inventory carrying costs by 31 percent. Luna: Thirty-one percent. That's not nothing. How did they do it without fancy tools? Lucas: It was a mid-sized manufacturer — I won't name them because the numbers are anonymized, but they make industrial components. The basic problem was that their inventory was always either too high or too low. They were carrying about forty-five days of safety stock on average, and still missing delivery dates. Luna: Sounds like every manufacturer I've ever met. So what was the first step? Lucas: They stopped treating forecasting as a purely internal exercise. The procurement lead, a woman named Sarah, realized that their forecast was built almost entirely on the sales team's gut feel, plus a three-month trailing average of orders. So she pulled in external data — things like regional weather patterns, because some of their components were tied to construction and outdoor projects, and also a shipping index that tracks freight volumes on the major routes. Luna: That's interesting. Weather and shipping volumes. But how do you get that data without spending a fortune? Lucas: That's the thing — most of it was free or cheap. Weather data from public sources, shipping indices from industry associations. The key was that she didn't try to build a predictive model. She just used those signals to sanity-check the sales forecast. If sales said demand would spike in May, but the weather data said the region was heading into an unusual cool spell, she'd question it. Luna: So it's more about asking better questions than running algorithms. Lucas: Exactly. And that's where the conversation with suppliers changed. Instead of just haggling over price per unit, Sarah started sharing her revised demand outlook with key suppliers six months out. She asked them, 'Can you commit to this capacity if we lock in a volume agreement?' That shifted the dynamic from transactional to collaborative. Luna: And the suppliers were on board with that? Usually they're wary of sharing capacity plans. Lucas: A few were, honestly. But Sarah offered something in return — firmer volume commitments and a longer contract horizon. In exchange for the suppliers' flexibility on short-term orders, she promised minimum annual volumes. That gave the suppliers the certainty they needed to plan their own raw material purchases. Luna: So it's a win-win. But what about internally? I imagine sales wasn't thrilled about someone second-guessing their numbers. Lucas: That was the hard part. Sarah spent months getting sales and operations to trust the new forecast. She didn't just present a new number — she showed them where the old forecast had been wrong, month by month, and what that had cost in expedited shipping and stockouts. Once they saw the direct financial impact, they came around. Luna: That's a good example of why procurement can't just be about the supplier side. It's about internal alignment too. Lucas: Right. And the results were pretty dramatic. Within two quarters, they'd cut safety stock from sixty days to about thirty-five, and service levels actually improved. They reduced inventory carrying costs by 31 percent, which for them was about two point four million dollars a year. Luna: Two point four million. That's real money. And it didn't require a million-dollar software implementation. Lucas: Not at all. In fact, the only new tool they used was a simple spreadsheet that combined the internal and external data. The real investment was time — getting people to trust the numbers and to collaborate with suppliers differently. Luna: I love that this is so accessible. It's not about having a PhD in data science. It's about asking the right questions. Lucas: Yeah, and that's something we talk about a lot on this show. And you know, if these conversations have helped you think about your own procurement challenges in a new way, we'd love it if you considered supporting the show. It's listener support that keeps this podcast ad-free and independent. You can do that at buy me a coffee dot com slash fexingo. No pressure, but it makes a real difference. Luna: Yeah, it really does. And we appreciate every single person who's done that. Now, back to Sarah — I want to dig into the specifics of how she actually built that forecast. Was there a particular method she used? Lucas: Good question. She didn't use anything exotic. She started with a twelve-month rolling average of actual orders, then adjusted it based on three external signals. First, weather data for the key regions where her customers were located. Second, the freight volume index I mentioned — if trucking volumes were down, that usually meant softer demand ahead. And third, she looked at her customers' own public announcements, like new product launches or factory expansions. Luna: So it's a blend of leading and lagging indicators. That makes sense. Lucas: Exactly. And she was careful not to overreact to any single signal. She'd adjust the forecast only if two of the three signals pointed in the same direction. That kept the noise down. Luna: That's a practical rule of thumb. I bet a lot of companies get burned by chasing every piece of data. Lucas: They do. And Sarah's approach was to keep it simple and transparent. She documented every adjustment she made and why. That transparency is part of what convinced the sales team — they could see the reasoning behind the numbers. Luna: So it's not just about the forecast itself, but about building trust in the process. Lucas: Absolutely. And that trust paid off in another way. Once suppliers saw that Sarah's forecasts were becoming more accurate, they started offering better terms — because they could rely on her numbers. That's when the real cost savings kicked in. Luna: Can you give me an example of a specific supplier that responded to that? Lucas: Sure. There was one steel fabricator that had always charged a premium for short-lead-time orders. After six months of consistent forecasting, Sarah negotiated a ten percent discount on those rush orders by committing to a minimum quarterly volume. That alone saved them about three hundred thousand dollars a year. Luna: Ten percent off rush orders — that's a big deal. And it came purely from trust built through better forecasts. Lucas: Right. And it's a good reminder that cost cutting in procurement isn't always about squeezing suppliers. Sometimes it's about giving them the stability they need to lower their own costs. Luna: So what would you say is the biggest takeaway for our listeners who want to try something like this? Lucas: Start small. Pick one product category, maybe two or three suppliers, and just start incorporating one external data signal into your forecast. Track the accuracy over a few months. You'll likely see improvements, and that will give you the evidence you need to expand the approach. Luna: And don't forget the internal buy-in. Sarah spent almost as much time with sales as she did with suppliers. Lucas: Yeah, that's the part that often gets overlooked. The best forecast in the world is useless if the sales team won't trust it. So bring them into the process early, show them the data, and let them challenge it. Luna: That sounds like a solid blueprint. I'm curious though — did Sarah face any pushback from her own procurement team? Sometimes it's hard to change the way you've always done things. Lucas: There was some, sure. A couple of the senior buyers felt like this was overstepping into sales territory. But Sarah framed it as a support function — she wasn't trying to set the forecast, she was trying to make it better. Once they saw the results, the resistance faded. Luna: It's amazing what a few million dollars in savings does for internal politics. Lucas: Exactly. And the other thing that helped was that Sarah tied her cost savings directly to the company's bottom line. She presented the numbers in a way that CFO could understand — reduced carrying costs, fewer expedited shipments, better payment terms. That made it a board-level story, not just a procurement win. Luna: So this isn't just about inventory — it's about the whole ecosystem of how you buy. Lucas: Right. And that's the angle I want to leave you with. Demand forecasting isn't traditionally seen as a procurement skill, but it's become one of the most powerful tools a buyer can have. It changes the conversation from price to partnership. Luna: And it's something any buyer can start doing tomorrow, with just a spreadsheet and some curiosity. Lucas: Exactly. So if you're looking at your own inventory and wondering why it's never quite right, maybe the problem isn't your suppliers — maybe it's the forecast that's driving your purchases. That's a good place to start. Luna: Well said. And for our listeners, we'll have a few links in the show notes to some of the free data sources Sarah used. Until next time, keep asking the right questions.