US Trucking Primer I: Cycle basics

Death on the Ridge Road - Grant Wood - 1935 (Wikimedia)

The trucking industry (and its upstream value chain links) have been in a deep downturn since the end of the post-pandemic (2021/22). The downturn is, by industry standards, the deepest and longest in a record of a few decades.

This narrative (repeated across so many backbone industries), plus the potentially accompanying cycle-low valuations, interested me in the industry.

The goal is the same as with other cyclical industries: find cost or margin leaders, financially strong, trading at low multiples of cycle-average profitability. And if those can’t be found, at least be prepared for the next leg of the cycle, while learning more about cyclicality, capital returns, leverage, and growth, in a very particular cyclical industry.

This article covers the industry basics: different segments across the value chain, their cyclicality, returns on capital, and secular growth; plus the specifics of the past cycle.

In a future delivery, we will analyze specific companies in some more detail.

You know, the first time I traveled hard

Out in the rain and snow

In the rain and snow

I didn’t have no payroll

Not even no place to go

On the road again - Canned Heat

Disclaimer: The opinions expressed in the Blog are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product.

The trucking cycle

Inelasticities in supply and demand

Let’s review what, at this point, is a mantra: cyclicality tends to breed from inelasticity at supply or demand. That is, one of the two sides (or both) cannot react quickly to price signals, therefore generating extended trending periods of excess or lack of supply. In the case of trucking, we have both types of inelasticity.

On the demand side, stuff has to move, and there are only so many ways it can be moved around. If trucking becomes expensive, then some businesses might try to move some freight to railroads (or barges if they are really cool), but that’s about it. Aggravating this, trucking’s upward/negative cycles tend to coincide with positive/negative consumer discretionary demand and business stocking/destocking cycles. If, say, shoes, are being sold like crazy, shoe stores will pay up for freight if it leads to getting more inventory. On the contrary, if shoes are not selling, shaving a few dollars of freight won’t make any business stock more.

On the supply side during the upturn, trucks and drivers don’t come out of thin air, so there is a lag to expanding supply, specially coming from a downcycle: truck OEMs may have low finished and component inventories, so orders start to pile up; and new truck drivers need to be trained, at a time which may coincide with labor market tightness (during the consumer discretionary upcycle). During the downturn, the main problems are depreciation and leverage: operators (many of which are really small) still need to pay for lease payments or interest on loans, even if they don’t cover the depreciation of the vehicle, therefore pressuring rates down.

Distinctive features

Besides the general drivers of cyclicality, the trucking cycle also has specific features affecting it. The most important ones, in my opinion, are the larger role of demand (and within this, discretionary demand), a low relative level of inelasticity, and the role of labor.

Relative importance of demand

Starting with the role of demand, whereas in many cyclical industries, supply ebbs and flows tend to be the driver of the cycle, with demand being more consistent over time or as a percentage of GDP, I would say that demand (or, should I say, cycle-affecting demand) is at least as volatile and relevant as supply in the trucking cycle.

The reason is that the marginal demand affecting the cycle is mainly driven by inventory cycles in discretionary or cyclical industries. The large majority of stable freight that makes up the bulk of the industry does not fully participate in the cycle because it is internalized or contracted under mid-term conditions.

Approximately 40% of all truck freight by value (excluding Parcel) moves in private fleets managed internally. This is particularly true for products with low value-density (low price per volume or kg), like some foods, CPG, and commodities, for which a cyclical increment in freight costs would represent a larger impact on margins. Of the remaining 60%, about 20pp are managed by trucking companies but operate exclusively with one client (a modality called Dedicated), or under other forms with more stable or contracted rates (like LTL). That leaves about 50/60% of the industry somewhat isolated from volatility (at least in the short to mid term).

The remaining 40/50% of the industry works fully for-hire (called truckload or TL) and is where the spot prices that mark the cycle are determined. This part of the market accommodates the unplanned, marginal needs of shippers, following the patterns of stocking/destocking. Stocking cycles tend to be more acute in discretionary sectors (apparel & footwear, furniture, appliances, electronics, automotive, etc) and in certain industrials. This is what connects the trucking cycle with the discretionary cycle and related factors like housing activity, purchase of durable goods, etc.

Relative importance of labor

In trucking, labor is a significantly more relevant factor than capital (depreciation of the trucks themselves) in costs, at least in the US. Labor costs can easily reach 50% of revenues in many trucking companies and segments, versus 8/15% for D&A. To this, we need to add the weight of owner-operator trucks in the market, where labor is masked as profit. So far, I have not seen a cyclical industry with close to that level of labor importance.

I believe labor tends to lengthen the cycle on the downside, both for companies and for owner-operators. Owner-operators can accept lower profit margins, which basically means they make less from their labor, as long as they cover operational costs and their lease/loan costs. They make labor a variable factor. In companies, labor can be a relatively fixed expense, depending on unionization or severance costs. If the driver is already paid, and the truck is already depreciating, then companies will prefer to make some use of them, even if at low rates.

On the upside, labor is probably not the most limiting factor, but it does collaborate with rates skyrocketing. For labor availability, the specific conditions of the job require some monetary enticement, and if the time coincides with a discretionary upcycle, then blue-collar workforce availability might be relatively tight. Training is probably not such a big factor, but two months is still the minimum it takes to get a very junior driver. Further, experienced drivers know they are in demand, meaning they can switch jobs if compensation is not updated. Finally, one driver cannot really produce much more freight with the same piece of capital. This all puts upward pressure on rates.

Finally, labor probably causes a secular uptrend in the size of the trucking industry, about in line with inflation, not correlated with real trucking volumes/weights transported. Labor is one of the tightest factors in an economy, and as explored in a specific article about the role of services in US deficits, wages can keep escalating without real productivity gains. The future role of robotics in trucking will probably change this factor, though, and make the industry more fully capital-driven.

Depreciation is real and more comparable to a cash-cost

In many cyclical industries, an old plant will continue generating product long after it has been fully depreciated. Its economic value may have decreased a lot because scale and technology change may render it uncompetitive, but the plant still works. During downturns, maintenance CAPEX in these industries can dip well below D&A without challenges.

However, in trucking, this is not the case. A tractor or trailer will break down much faster. Most carriers renew their tractors within 3-5 years and their trailers within 8 years. This implies that D&A is a real expense, which cannot be under-expensed in cash for a long time, because otherwise the “usability” of the capital base decreases. If the same truck can still ride, it will need to ride slower, or spend more days every year at the mechanic, etc., decreasing the productivity of the fleet.

This increases the cash constraint on carriers during downturns, accelerating the exit of supply.

Relatively short cycle

Moving to the length of the cycle, within the classification of cyclical industries (for more on this, see my Cyclicals Framework), I would say trucking is a fast, narrow cycle, the reasons being that inelastic factors are not as strong as in other industries.

On the demand side, we saw above that one big driver of the cycle is the marginal inventory cycle of discretionary industries, which tends to be relatively short and can invert quickly (going from under to over-inventoried and back relatively fast). This does not mean demand is elastic (it is not high freight prices that cool demand), but rather that it is volatile.

On the supply side, players are highly atomized (small owner-operators are common), meaning supply can adapt in more marginal increments, compared to large capital investment industries, where supply additions/subtractions happen in chunks.

We can observe below the Cass Linehaul Index, which tries to capture the ‘bare’ cost of freight, without the impact of fuel or other accessorials. A factor not accounted for by the Cass Linehaul Index is the cost of labor, which, as mentioned above, I believe has a cross-cyclical upward effect on trucking rates.

The super-cycle of 2021/25 and its lessons

The downward leg of the cycle the industry is currently in, and its previous upcycle, have both been extreme.

The volume of shipments (Cass Freight Index - Shipments) has been falling every month since January 2023. The aggregate volume of payments for freight services (for-hire and contract), captured by the Cass Freight Index - Expenditures below, shows a little more stabilization, but this includes the secularly upward force of inflation. Carrier and logistic operating margins were still decreasing as of 3Q25.

Such a downturn was caused by an even more extreme upturn before it, leading to a massive overhang in the market, which, added to slow growth in goods, durable, and industrial categories, all led to a prolonged slump.

The 2021/22 upcycle combined everything needed for a ballistic bull market: disruptions in the supply chain leading to a fight for inventory across all goods industries, those same disruptions restricting the production of trucks by OEMs, labor was hard to come by, and the stimulus and the post-pandemic consumption boom fueling explosive demand. The only priority of businesses back then was ‘get your hands on inventory, because it will sell’. In many relatively high value-density categories (apparel or footwear, for example), flying inventory was normal. We also had factors pushing the price of freight up, but potentially not the margins: fuel, labor, spare parts, and insurance costs all going up.

In the aftermath, there was a huge bullwhip effect: trucks were now plentiful (OEMs producing at full capacity), and the inventory cycle had completely turned to destocking as much as possible. This led to the first big slump in prices and shipments. What has kept the cycle sluggish, in my opinion, is now more related to weak durable goods demand (auto, appliances, furniture), all related to high interest rates and low housing demand (chart below), and weak industrial production (manufacturing PMI in contraction levels for almost 36 months).

I have two takeaways from these extremes.

First, the upside portion is very unlikely to repeat, as it was caused by a rare combination of booming demand at a time of widespread collapsing supply chains. Today, probably many supply chains are low on inventories, but demand will not suddenly explode out of accumulated savings and stimulus money globally.

Second, although peppered by smaller cycles, a long-term less profitable trucking market is consistent with industrial and goods demand being sluggish. Trucking supply is eventually removed from the market, ultimately via the work of physical depreciation, but if demand does not grow in a trend, it is unlikely that the trucking cycle can have significant undersupply.

Trucking segments and their returns

The different types of services that encompass a transportation supply chain can be sliced into many different ways, leading to trucking having almost a dozen sub-segments. Most companies participate in several of them at the same time, but have one or two in which they are more focused.

The first slice we can make is between owning tangible assets like trucks or docks and only contracting/brokering them. The first type of companies is called Carrier, and the second are Logistics/3PL/Brokers.

This distinction in tangible assets already implies different economics.

In a tangible-asset-heavy company, growth in revenues and growth on the balance sheet are evidently linked. The actual returns on capital will depend on other factors (the highest return on capital companies in trucking are tangible-asset heavy), but still, assets are needed. The need to finance growth is relevant when evaluating yields and returns below, especially for relatively low-return companies (<10% post-tax).

Logistic companies, who branded themselves as ‘asset-light’, we should say ‘tangible-asset-light’, really, should theoretically be able to sport higher returns on capital, because scale is decoupled from the balance sheet. Unfortunately, low barriers to entry tend to make competition and growth hard. The majority of these companies show growth by acquisition, with intangibles and goodwill representing a good portion of the balance sheet. They are, therefore, ‘intangible heavy’. If they decided not to grow, potentially their cash returns should be good, but this is rarely the case.

Within carriers, we have several sub-segments, based on the type of goods transported and service provided. Here, the most relevant economic distinction is the complexity of the shipment, and consequently of the network needed. This is somewhat inversely correlated to the size of the shipment.

In terms of types of goods, we have dry, refrigerated, and specialty (cars, livestock, chemicals, farm products). This segmentation does not introduce a lot of economic differences.

Then, we have the size of the shipment: truckload (TL), less than truckload (LTL), and parcel. This introduces a lot of economic distinction.

In a truckload shipment, the whole trailer is used for a single shipper (the company sending the goods). For the carrier, this is a simple job: pick the trailer, move it, drop it. The asset network required to provide such a job is relatively simple: trucks, trailers (this could be property of the shipper), and a series of docks for unused assets (trucks or trailers) to be dropped when not used. Low complexity means low barriers to entry, i.e., more competition and lower returns on capital. Of course, there are benefits to scale, like having higher asset utilization, or sharing other assets and overhead (maintenance, admin, etc.), but this is not a huge barrier.

Within truckload, we can differentiate three specific modes. The simplest is one-way truckload (pick, transport, drop), which is arguably the most commoditized and more exposed to spot rates. Another important mode, particularly for public companies, is dedicated, that is, the company manages fleets that operate for specific clients, usually doing scheduled routes. Dedicated is affected by the same commoditization and depends on the spot market, but contracts can be longer, and therefore, cycle volatility is a little lower. Finally, we have intermodal, which is a mix of shorter truck hauls (called drayage) and longer railroad hauls. I don’t find intermodal has a lot more barriers to entry, because the key network assets are owned by the railroads, not the trucking carriers.

Less than truckload is much more complex than truckload. The shipper cannot simply load a trailer, because it will not be full. The carrier has to pick the goods (usually on a smaller hub network), bring them to the hub, consolidate them with other goods sharing the same destination in a larger truck, move them, and then invert the process (separate and deliver). Scale has a larger role here because the overhead is much higher. The hubs are larger, have more staff, and need to be granular enough to provide good transportation economics. This naturally leads to more concentration. The top 10 LTL companies make up 70%+ of the US market, versus less than 5% for TL. In addition, the client that requires LTL tends to be smaller, because otherwise it would make better use of a full truckload, having more distribution centers and such. This also helps with bargaining power (smaller/weaker client). LTL is at the top of capital returns, at least since the GFC.

The last within tangible-heavy sub-segments is Parcel, which is like a micro-LTL, requiring the most complex type of network. We find that concentration is the highest, with 3 companies (FedEx, UPS, and USPS) owning 85% of the market, excluding Amazon, which handles its own mostly internal network; if we account for Amazon, these 3 drop to 65% nonetheless. In terms of clients, Parcel networks potentially serve the smallest ones, which can’t reach LTL-levels on long-haul freight (the local/regional portion of Parcel can be handled by last-mile delivery companies, which are way less complex and more commoditized). Finally, their size is gigantic, each of FedEx and UPS generating 1.5x as much revenue as the whole LTL market (FedEx’s own LTL arm is the largest in the market and makes up only 10% of the company’s revenue).

These should generate the highest returns on capital, but they don’t. Some reasons I can think of are some diseconomies of scale (too much granularity makes it hard to reach utilization, pushing on price competition to increase volumes), more transparent pricing, higher service expectations from the e-commerce economy, etc. Another one is the weight of leases (18% of the balance sheet for FedEx, 6% for UPS), which should be part of the denominator (they are assets needed for the operations of the business) but potentially not of the numerator (as the D&A recorded for ROU might actually be a compensation to capital).

Finally, we have the logistics/3PL/brokerage companies. What joins these companies is lower ownership of tangible assets (mainly long-distance tractors), albeit not always.

There are several subsegments, with most of the companies operating in several of them. Pure brokerage is maybe the more intangible, connecting shippers with carriers (CHRW, RXO, LSTR as purish-plays). Managed transport adds some more planning and freight admin work management for the shipper, something like a dedicated brokerage. Fulfillment and consolidation imply owning warehouses that can aggregate shipments, like a mini-LTL network, without the trucks, but still asset-intensive (GXO). There is also truck leasing (R as purish-play), which is asset-intensive but also not trucking per se. We can observe that high tangible-asset companies (GXO, R, HUBG) do not have the best returns on total assets.

In some cases (RXO, FWRD, GXO), it is also the weight of intangibles and goodwill, coming from acquisitions, that depresses the return on assets. On a forward no-growth basis, intangibles and goodwill are not actually assets needed to run the business, but in reality, these companies tend to grow by acquisition, and therefore need to deploy capital to intangibles and goodwill. This is why I have used Total Assets instead of Tangible Assets for these companies.

The two best returns (CHRW and LSTR) both compete in the less tangible area and have done fewer acquisitions.

Conclusions

Trucking is currently in the deepest downturn in recent memory, and has some companies with attractive decade-average returns on capital, which may at some point become cheap and attractive.

This requires careful threading, though. These are generally capital-intensive, not super high-barrier-to-entry businesses, where earnings can be fully absorbed by capital needs.

The next delivery of the series will be an overview of the companies, with valuation metrics to help us understand potential future returns under different scenarios.