Latest / The Pivot Podcast with Fexingo: How Businesses Change Direction and Survive Disruption / How UPS Turned Logistics Into a Data Business
Transcript
- Lucas: Let's talk about a company most of us interact with at least once a month but rarely think about as a business story: UPS. Luna: The brown trucks. The uniforms. The delivery guy who leaves your package on the porch. What's the pivot there? Lucas: UPS started in 1907 as a messenger company. For most of its life, it was just about moving things from point A to point B. But around 2015, something shifted internally. They realized that the data they were collecting from every package, every truck, every route was potentially more valuable than the delivery itself. Luna: Wait — more valuable than the delivery? That's a big claim. Are they actually making more money from data than from shipping? Lucas: Not yet. But the trajectory is clear. In 2020, UPS generated around 84 billion dollars in revenue. About 800 million of that came from what they call 'value-added services' — which is mostly data analytics. It's still small relative to the core, but it's growing at about 15 percent annually, while shipping revenue grows at maybe 3 percent. Luna: So the pivot isn't complete, but the direction is set. What was the specific moment that triggered this? Lucas: I'd point to two things. First, the ORION system — that's On-Road Integrated Optimization and Navigation — rolled out fully in 2016. It's an algorithm that calculates the most efficient route for every single driver. UPS says it saves them 10 million gallons of fuel a year. But the bigger insight was that ORION generated massive amounts of data about traffic patterns, delivery density, customer behavior. Luna: They basically built a real-time map of American commerce. Lucas: Exactly. And once they had that map, they realized they could sell access to it. Not the raw data, but insights. For example, a retailer can use UPS data to figure out where to open a new store, because UPS knows exactly which neighborhoods are ordering what products. Luna: That's pretty powerful. But isn't there a privacy issue? I mean, they're tracking individual packages. Lucas: They anonymize everything. They're not selling 'John Smith ordered diapers on Tuesday.' They're selling aggregate patterns: 'In this ZIP code, baby product deliveries increased 20 percent quarter over quarter.' It's the same kind of data that credit card companies have been selling for years. Luna: Okay, so second thing? You said two triggers. Lucas: The second was the creation of UPS Capital back in the late 1990s, but its real pivot into a data-driven lending business happened around 2018. UPS Capital started offering small business loans based on a company's shipping history. If you ship a lot of packages with UPS and you pay on time, they'll lend you money at better rates than a bank would. They're using their own logistics data as a credit score. Luna: That's genius. They have data no bank has — actual transaction volume, not just a credit report. Lucas: Right. And they've lent out over a billion dollars so far. Default rates are lower than industry average because the data is predictive. A company that ships consistently is a company that's operating. Luna: So the pivot is really about monetizing the byproduct of their core business. I'm reminded of how Amazon turned its logistics into AWS — but UPS is doing it without building a separate cloud business. Lucas: That's a great comparison. But UPS's advantage is more subtle. They don't have to build a new customer base — they already have millions of businesses shipping with them. The question is whether they can scale these data products fast enough to matter. Luna: What's the biggest risk you see? Lucas: Competition. FedEx is doing similar things. DHL has its own analytics. And then there's Amazon — which is both a customer and a competitor. Amazon is building its own delivery network, and they're arguably better at data than anyone. If Amazon starts offering logistics data services, UPS could be squeezed. Luna: But Amazon's network isn't as big as UPS's yet. UPS still delivers about 25 million packages a day. Lucas: That's true. And scale is a moat. But the clock is ticking. UPS needs to make the data business a much bigger chunk of revenue before the core shipping business gets commoditized. Luna: Commoditized by whom? Amazon? Regional carriers? Lucas: All of the above. Shipping is increasingly a low-margin business. The average profit margin for a package is only a few cents. Data services, on the other hand, have margins of 40 to 60 percent. So the pivot isn't just a nice to have — it's existential. Luna: That makes me think about what other industrial companies could do this. Like, what about a company like Caterpillar or John Deere? They're sitting on huge equipment data. Lucas: Exactly. John Deere is already doing it — they sell data subscriptions to farmers for precision agriculture. But UPS is interesting because it's a logistics company, not a manufacturer. Their data is about commerce, not machinery. It's more broadly applicable. Luna: Let's get concrete. Can you give me an example of a specific data product UPS sells? Lucas: Sure. One is called 'UPS Delivery Planner.' A small business can pay a monthly fee to get optimized delivery routes for their own fleet. It's basically a stripped-down version of ORION. Another is 'UPS Market Insights' — retailers can subscribe to get reports on what products are trending in different regions, based on shipping volume. Luna: So they're packaging their internal tools and selling them back to the same customers who ship with them? Lucas: Yes. And those customers are already in their ecosystem. The switching cost is low for the customer, but the value is high. If you're a retailer using UPS anyway, why not also use their data to decide which products to stock? Luna: That's a smart bundling strategy. But I wonder — does this actually change how UPS is valued by investors? Lucas: It's starting to. Traditionally, UPS trades at a price to earnings ratio of about 15 to 18, which is typical for a logistics company. But if they can convince the market that they're a data company with a logistics arm, that multiple could expand to 25 or 30. That would add tens of billions to their market cap. Luna: So it's as much a financial pivot as an operational one. Lucas: If today was actually useful to you, the way these stay ad-free is listener support. Buy me a coffee dot com slash fexingo. It's a small thing that keeps us independent. Luna: Yeah. We don't do sponsors, we don't do ads. Just people who find value here. So if that's you, thank you. Lucas: Alright, back to UPS. The other dimension I want to touch on is how this pivot changes the culture inside the company. UPS has always been very operational — drivers are trained to the second. Now they're hiring data scientists and software engineers. That creates tension. Luna: I bet. The old guard probably sees data as a distraction from getting packages delivered on time. Lucas: And there's some truth to that. If a data project takes resources away from route optimization, you might see a short-term dip in service. But the CEO, Carol Tomé — who took over in 2020 — has been explicit that UPS is a 'technology company with a trucking problem.' She's pushed for more investment in analytics. Luna: How much are they spending on tech? Lucas: About 4 billion dollars a year on technology — that's almost 5 percent of revenue. For comparison, FedEx spends about 2.5 billion. So they're outspending their closest rival significantly. A lot of that goes to data infrastructure and machine learning. Luna: Is there a risk they overinvest and the data business never materializes? Lucas: Sure. It's a bet. But even if the data products don't become a huge revenue line, the investment in ORION and analytics already saves them money in fuel, labor, and maintenance. So it's not a pure gamble — there's a real operational return. Luna: So the pivot has a floor. Even if the upside doesn't fully materialize, they're better off than before. Lucas: Exactly. And that's what makes it a smart pivot rather than a desperate one. They're not abandoning their core — they're adding a layer on top. The trucks still deliver packages. But now every package generates a data point that can be sold, analyzed, or used to make the system more efficient. Luna: I want to ask about the competitive response. FedEx has their own data initiative, but they've been slower. What's their equivalent? Lucas: FedEx has 'FedEx Dataworks' which they launched in 2021. It's similar in concept — using shipping data to provide insights. But they're behind. UPS had a five-year head start with ORION. And FedEx's culture is more decentralized, which makes rolling out a unified data platform harder. Luna: So UPS has a window. How long do you think it lasts? Lucas: Maybe three to five years before FedEx catches up or Amazon enters the space. That's why they're moving fast. In 2025, they launched a new API for developers to integrate UPS data into their own apps. They're trying to become a platform, not just a service. Luna: A platform for logistics data. That's a big ambition. Lucas: It is. And it's not unprecedented — look at what Shopify did for e-commerce. They started as a tool and became an ecosystem. UPS wants to do the same for shipping. The question is whether a 116-year-old company can move with that kind of agility. Luna: What's one metric you'll watch to see if the pivot is working? Lucas: I'd watch the share of revenue from 'supply chain and freight' — that's the segment where they report data services. If it grows from the current 17 percent to 25 percent over the next five years, the pivot is real. If it stays flat, they're just a trucking company with a nice algorithm. Luna: That's a clear benchmark. So to sum up: UPS is using its operational data to build a higher-margin business, but the clock is ticking. Lucas: Exactly. It's a race between internal transformation and external competition. But they have the data, the scale, and the head start. Now we'll see if they can execute.