The Poor ROI of Autonomy

A Product Dive on how most ROI comes from Unmanned Remotely-Supervised Trucks

This is the second in a multipart series I’m calling “Opening the Starsky Kimono” where I share Starsky strategic insights that we previously considered top-secret.

True autonomy is worth almost nothing when it comes to trucks. For robot-driven unmanned trucks, or robotrucks, the magnitudinal improvement actually comes from solving the driver shortage the efficiencies fleets can focus on once they’re no longer preoccupied with the hiring and retention of drivers. Per dollar invested, making a robotruck truly drive itself has the least ROI of all of those improvements, which is fortunate because it’s also the least likely to happen.

At Starsky we modeled that our robotrucks could achieve 42% margins even if each had a dedicated remote person paying attention 100% of the time. Those margins would jump to 58% if that remote driver only needed to pay attention for the first and last miles.

True autonomy, on the other hand, would have added less than 2% to our bottom line. Which means that the technological achievement $70b has been invested in over the last decade is worth less to the trucking industry than automatic billing.

What!?

The US trucking industry is structured around the systemic shortage of long-haul truck drivers. The 3.5 weeks/mo an over-the-road (OTR) driver is expected to spend in a truck is so miserable that few will do it for even $60k/yr. On the other side, trucking is a highly fragmented commoditized industry, which puts no fleet in the position where they can raise prices sufficiently to afford to pay drivers more. The result is that the market typically has at least 50,000 too few drivers to meet demand.

Source: “Truck Driver Shortage Analysis 2019,” ATA

This shortage defines everything in American trucking — it’s why our trucks have nice comfortable cabs (worse fuel efficiency but better driver retention), it’s why our railroads are so profitable (which is why Warren Buffet buys them), and why our supply chain has even been shaped to minimize how much time trucks need to drive in cities (drivers get paid by mile and hate driving in slow-speed cities).

One is more fuel efficient and maneuverable, the other is more comfortable to live in

On a fleet level, almost every trucking company has more demand than it has drivers. That means that the easiest way to increase profit is almost always to add more drivers. Platooning or automated dispatch would save fleets plenty, but almost every fleet would see better ROI if they instead invested in driver hiring and retention. As a result the industry invests in little outside of drivers.

That changes when you no longer need the driver in the truck. $60k/yr isn’t enough to entice over-the-road drivers but it is more than enough to recruit drivers who get to sleep at home. Without the pressure of the driver shortage fleets can tackle the problems the industry has traditionally neglected and change the traditional economics of trucking.

Trucking Economics

Trucking is a business with both high fixed and variable costs. For every dollar that comes in, the best run firms typically spend 75% of it evenly divided between fuel, equipment, and labor. They then spend another 17% or so of administrative overhead per truck before eking out an 8% profit margin.

The variability of truck drivers is part of why these costs are so hard to control. A driver may be willing to drive 25 days in May but only 20 in June so as to make it home for a family event. Still harder to manage, a different fleet may offer your driver a lucrative signing bonus which causes them to abandon your truck far afield from your office, which might effectively make your truck sit idle for a week and then cost money when you recover it.

That isn’t really a risk when it comes to robotrucks. While the AI system might have fits, it should be fairly predictable. A robotruck will never demand to go in an inefficient direction so as to be at their kid’s birthday. They’ll never quit to work for a competitor who pays more. They’ll never demand to replace a truck with uncomfortable seats.

The greater predictability of robotrucks allows for costs to be optimized like never before.

Fuel

Through a number of means, at Starsky we thought we could decrease our fuel spend by at least 20%, increasing base profit rate by 62%.

At peak Starsky spent over $150k/mo on fuel across our 50 truck fleet. Where big dollars are spent, savings can be found.

Increased fuel economy from smoother acceleration and deceleration, as well as the weight cut by eliminating the sleeper cab should save robotrucks 7.5–10% of their fuel consumption. 7.5% volume discounts are common for larger fleets from major truck stops. Some of the more sophisticated fleets use fuel futures to save 15–20%.

A Starsky truck a Miccosukee Service Plaza in FL where we would often teleop right to the pump.

Much of the inefficiency in fuel purchasing, however, is human driven. Starsky’s $150k in monthly fuel spend was across 250 truck stops. Even if all those trucks were on the same route purchases would be spread across 10–20 truck stops, simply because it’s hard to schedule your drivers’ bathroom breaks.

But what if you could perfectly concentrate your fuel purchasing? $150k is 5–10% of monthly income for many truck stops. If a fleet only purchased fuel from one gas station per route, you should be able to purchase it for cost plus.

In total we modeled that we could save at least 20% of our fuel spend, bringing it down to 20% of gross. That would bring the overall profit margin of robotrucks up to 13%.

Equipment

By not needing a sleeper cab, self-insuring, and scale in a fragmented market we thought we could cut equipment costs by 40% which alone would increase profit 125%.

The 25% of gross, or $0.50/mi, that trucking companies spend on equipment is one of the harder costs to manage. The vast majority of it, or about $0.40/mi, goes into the purchase, maintenance, and depreciation of the tractor and trailer. The remaining $0.10/mi pays for insurance.

By the end, at Starsky we paid about $0.30/mi in fixed costs if our average truck drove 8200 miles/mo (a minimum that would have been considerably lower if we owned and didn’t lease our trucks). We then had a variable cost of about $0.10/mi to cover maintenance split 70:30 between the tractor and the trailer.

The most expensive part of this equation is the tractor. While a daycab (a truck without room for the driver to sleep) costs about $100k, a sleeper cab is typically $165k at list price. If you don’t need a driver to sleep in the truck, you don’t need a sleeper cab which allows you to immediately knock $65k off your fixed costs. At scale we projected that we could buy day cab tractors for ~$75k which would lower our cost per mile by about $0.12, or a savings of 16% of gross.

A mockup of a v2.0 Production Starsky-equipped Day Cab, which should have cost less than a normal truck.

Since the Starsky robot primarily relied on cameras, our entire system cost only about $65k last June — without any scale our unmanned day cab would cost as much as a traditional truck. In time we expected our system to cost about $10k which would put our equipment cost at a thrifty $0.30/mi.

Insurance is another opportunity for cost optimization. An owner-operator truck driver might spend $12k/yr on truck insurance and a fleet with 10–50 trucks might spend $7000/truck/year. The big fleets, however, are able to see large savings by self-insuring.

Truck deductibles are typically over $10k. The most expensive risk to insure is all of the liability from the $10,001th dollar to the $500,000th, which is what fleets are spending $6500 of the $7000 premium on. If that money is instead escrowed aside you can instead buy insurance on just the relatively cheap risk above $500k. That would make your cash outlay for insurance a mere $500/truck/yr, or less than $0.01/mi.

Factoring all listed above, a safe autonomous trucking fleet should spend only 15% of gross on equipment instead of 25%. That would bring robotruck profit margin up to 23% when added to fuel savings.

Admin

By making the backoffice of trucking as automated as Uber we thought we could cut the admin costs of trucking by 2/3rds, which would increase profit relative to normal trucking by 140%

Due to it’s high stakes-high volume nature, the trucking industry has been largely reluctant to adopt new technology over the last 30 years and as a result most trucking fleets run on software and processes that would drive a tech entrepreneur crazy. It isn’t uncommon for a fleet to have 3 fulltime payroll people per 100 trucks, or a dispatcher per 15 trucks, or for dispatchers to spend hours a day telling shippers where their freight is…all tasks whose automation are table stakes for on-demand startups.

Starsky’s in-house automation for running a trucking fleet, Hutch.

Trucking companies spend at least 17% of their revenue doing tasks that Uber spends zero incremental dollars on. We estimated that fully automating dispatch alone could save us upwards of $5000/truck/year. Even automatically ingesting paper Bills of Lading into our TMS could save us $500/truck/year.

In total we conservatively thought we could eliminate 2/3rds of overall trucking admin cost to bring it down to 5% of gross; bringing our profit margin up to 35%.

Labor

Almost all labor savings come from eliminating highway supervision and then from decoupling the driver from the truck.

The vision of autonomy has been that a computer program capable of driving everywhere with zero marginal cost can easily replace the $60k drivers earn per year, representing 25% of what the truck brings in.

The problem though, is that vision seems to require a number of asterisks; most notably that those systems won’t be able to drive everywhere. At least $70b has been invested in trying to make that vision reality, but so far no one has been able to deploy unmanned systems at scale. It seems unlikely a breakthrough will happen any time soon.

Just the improvements above would allow for a trucking company to more than triple its margins. Without counting on breakthroughs in AI, it is possible to decrease the labor cost of operating a robotruck.

Decoupling the driver from the truck is the easiest way to cut labor costs.

Decoupling the driver from the truck is the easiest way to cut labor costs. American truck drivers are paid only for the miles they haul freight — the hours spent waiting to be loaded or unloaded and taking mandatory breaks are all unpaid. As a result, the $200/day drivers typically earn is really only for the 7 hours/day they move freight and not for the 14 total hours they’re on-duty. This delta is big — it means that the trucking company feels like they pay drivers $28/hr while drivers feel like they only get $14/hr (or $8/hr if you consider the 24 hours/day drivers spend in a truck).

An early, ultra-light UI version of Starsky teleop circa 2017

Drivers who aren’t physically in a truck don’t need to lose productivity when the truck stops moving. Rather than twiddling their thumbs at a distribution center the driver could simply switch to a different truck in the fleet which has been loaded and is ready to move. The driver actually cares about earning $200/day — if they earned that by driving for 11 hours (vs being on duty for 14) their hourly rate would increase. The fleet would see their $200 buy them 57% more hours of a truck moving which would drop their labor cost by 30%, bringing it to just 17.5% of gross.

As a result a robotruck which is remotely monitored 100% of the time by a teleoperator who is looking only at that truck while it moves would cut labor cost from 25% of gross to 16.5% and have profit margins of 42.5%. Not bad for an MVP.

95% of the hours an OTR truck moves is on the highway. If you were able to eliminate remote supervision for the bulk of those hours you would see per-truck labor cost drop to just 1.75% of gross and profit margin would soar to 58%.

The hardest 1% of the technical problem, automating the surface streets and interchanges, would end up being worth only about $600/truck/yr. Level 4 truck autonomy has less value than a daily coffee.

Level 4 truck autonomy has less value than a daily coffee.

So What?

In Y-Combinator they tell you to make something people want. By which they don’t mean to build something your engineers want, but that your customers want. The US trucking industry wants a steady supply of trucks, and don’t particularly care if they’re autonomous or not.

If the industry doesn’t care about higher level, or L4, autonomy; if it’s really hard to build; and if it barely improves the margins of a robotruck fleet, then why build it?

At Starsky we always kept an eye on the business that we were building, which allowed us to tightly narrow the definition of our product.

At Starsky we always kept an eye on the business that we were building, which allowed us to tightly narrow the definition of our product. The high margins of unmanned but supervised trucking allowed us to sidestep most of the hardest parts of autonomy. If our robotrucks only drove as much as regular trucks we would make about $270k/truck in revenue or $156k in margin; which means 10,000 robots would make us $2.7b/yr.

That figure isn’t important because of all the cool things you can do with billions in margin, but because of all the things you don’t have to do to get to that size. Regulations in France not amenable to unmanned rollout? Don’t need to deploy there. Autonomous driving in snow appears to be an open research question? Don’t drive where it snows. Highway driving difficult at night? Drive only during the day. Connectivity not good enough everywhere? Only drive on roads with good connectivity.

Once you stop focusing on the quagmire which is true AI, the solvable challenge of designing a system safe enough for an unmanned test becomes paramount.

If L4 autonomy is worth little more than L3, which is worth only 30% more than L2; it becomes pretty clear that the primary focus of a robotruck startup shouldn’t be autonomy. It should be to make the simplest possible system that can complete a trip without a person in it. Once you stop focusing on the quagmire which is true AI, the solvable challenge of designing a system safe enough for an unmanned test becomes paramount. Which is exactly what we were able to focus on at Starsky.

-Stefan

Bonus: Increasing the topline

Robotrucks should be able to easily garner a 50% premium

The above improvements assume two easily disprovable assumptions: that robottrucks will earn the same revenue per mile as regular trucks and that they’ll drive no more hours a day.

The first assumption is easy to disprove. We found that not only did brokers not expect a discount (there is a shortage after all) but that in time we would be able to charge a premium because of a higher quality of service.

Sometimes your drivers just don’t show up. (Credit: Southern Dock Products)

Most OTR fleets have greater than 100% in annual turnover, with most drivers quitting with little to no notice. If you’re expecting 100 trucks to pick up yoru freight tomorrow, it wouldn’t be unusual for only 95 to show up. Larger fleets can actually charge a 25–50% premium to be held accountable — if you want to guarantee that they’ll have 100 trucks you need to pay more. Given that robotrucks won’t call in sick, it should be easier to earn that premium.

The second disprovable assumption is that robotrucks will drive no more than a traditional truck. This was modelled in both for ease of comparison (it affects fixed equipment cost in interesting ways) and because it gives the robotruck 17 hours/day to wait out conditions that are currently difficult for autonomy. It should be fairly easy for robotrucks to drive 16–20 hours a day which allows for faster delivery. Traditionally that’s only accomplished by having two drivers in a truck, which adds about 50% to trucking’s price per mile.

A good benchmark for trucking rates is $2/mi in revenue. With these two premiums robotrucks should be able to garner $3/mi fairly easily.

If cost decreased from $1.80/mi to $0.80/mi with all of the improvements listed above then robotrucks (unmanned but supervised 10% of the time) should get a 73% margin.

Which is pretty good, for a product in such demand that I’m still getting calls from brokers.

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