How data will eventually impact residual value, total cost of ownership, and transform heavy-equipment financing.

“Hours of use, type of use, and maintenance record. These are the three things that matter when calculating residual value,” said a former director of a major OEM’s financial business. While it’s hard to find anyone who would dispute that information has value, is more information necessarily good information when it comes to residual value?

“Don’t overthink it,” cautioned the finance professional, who has left the OEM for another business and agreed to bounce around ideas off the record. “Was the bulldozer used 2,000 hours per year in a single shift? Or double that? Was the ADT used to haul mine tailings, or did it transport feathers? Was the backhoe professionally serviced? Or was the owner a DIY type?”

At the moment, the prevailing wisdom seems to be that hours of use, type of use, and maintenance record — the Holy Trinity of residual value — adequately serve the industry’s purpose.

A used-car model

Dr. Rafał Sornek, Senior Vice President of Technology at Fortaco Group, makes the case for data impacting residual value.

“Take data OEMs already collect, store it in a public place, authenticate it with blockchain, and give industry professionals access to it.” Sornek’s proposal is to do for the off-highway industry what has already been done for used cars in Europe. “I can use a VIN to see a vehicle’s entire history. Why not do the same for a used crane?”

Sornek’s vision is massive amounts of data contributing to more accurate residual value, resulting in a lower total cost of ownership. “Even in an honest marketplace,” he argues, “sellers themselves sometimes don’t know what they’re selling.”

What OEMs know

Chris Domagala, CBDO of Lectura, a German- and Czech-based company which collects and sells transactional data on heavy machinery, says OEMs don’t always know as much about their assets as they let on. “OEMs have huge distribution- and dealer networks that sometimes show significant price autonomy. There are cases where the OEM doesn’t even know exactly for how much their machines went to market. They may not get data back from dealers. OEMs are experts on machine specs — they know which components break fastest — but not market prices.”

Domagala offers an example of how residual values are still handled on a higher “aggregation level” than they could be at financial institutions (the majority of assets in most countries belong to banks). “It depends on the institution, but crawler excavators, for example, are generalized on a rather high level. You’ll see it’s a 20- or 30-ton crawler excavator from a first- or second-tier manufacturer, and that’s usually it. Thus, the residual values they use are aggregated. But the more you know about your particular asset’s value development, the better you can calculate risk, the more profitable it can be. There are more and more ways to approach the car market’s transparency regarding rather accurate model-based value estimates.”

Change begins with a process of mutual educational, he says. “Bankers in the risk department have been in their jobs for 35 years, and to have a third-party company say ‘Our data knows more than yours and your experience’ isn’t always welcome. Also, vast smart data can fail. Banks will naturally take a defensive posture if the process is not symbiotically designed. There is also, literally, a lot that data can learn from ‘old stagers.’”

While collecting data isn’t at all new, putting it to good use is. “We’re not in the Dark Ages of collecting data, but we’re still at the beginning of connecting data,” says Domagala.

A new type of finance company

Michael Rohmeder is CEO of Equippo, which he characterizes as “a full-service marketplace for construction equipment” with a telematics project. Equippo might be thought of as the Zappo’s for excavators, offering online sales of inspected, delivered, and guaranteed equipment.

Depending on how you count it, the annual global transaction volume of used heavy equipment ranges from 100 to 300 billion dollars. Equippo’s goal is to get its customers the highest price possible for their equipment, with a high residual value and the lowest possible total cost of ownership. “The components of TCO are the new price, maintenance cost, and the resale value,” says Rohmeder, “and data can impact these heavily.”

Rohmeder says banks will write a seven-year contract with a residual value curve so they won’t lose money if the value turns. He sees room for a new type of finance company that derives benefit from connected data. One that might offer higher residual value thanks to smart data models, knowledge of future use, and maintenance, allowing the financer to be more aggressive on residual value and still make money.

“A starting point might be in the financing of extremely high-value equipment like cranes,” he says, which can sell new for over a million euros. But when purchased used, he notes, “Crane hours don’t convey how much it’s actually lifted. It’s an indication, but sometimes the crane is moving up and down with no load. What if we could prove with telematics data that the boom was only used to lift 20 percent of the time?” It’s the grandmother-only-drove-it-to-church scenario. Grandma may be telling the truth, but data could tell us whether she had a habit of riding the clutch.

Persuading the bankers

Since interest rates can represent 30 to 50 percent of total ownership costs, it’s a matter of time before things begin to change. Chris Domagala says a proper consortium must be built. “We need suppliers like Fortaco with deep knowledge of steel structures. Then we need an OEM with telematics data, a data company like ours, and then a tech provider who can build safe ways of data transfer.”

Domagala praises JCB as a first mover. “They launched a telematics platform for JCB users which gives you an overview of all JCB machines, where they are, and all telematics data on one dashboard. It’s impressive. But you’ve got to be an accredited JCB customer, it applies to JCB machines only, and it’s not even semi-public.”

“Bankers can be persuaded,” he says. The risk buy may be intimidated but the CEO will think differently. The bankers will eventually be in favor of it, and they have pull with the OEMs. It could happen in as fast as a year, if an OEM is willing to share historical data.”

Join the cause

Rafał Sornek hasn’t named the group yet, but he’s talking to anyone who’ll listen. He’s convinced Rohmeder and Domagala. And he’ll get around to convincing you, too.

“I want to appeal to people to be part of this project,” says Domagala. “The more people we have at the table, the better the results, and the better we can build trust. Think about a machine’s decreasing residual value curve and the upward-sloping cost development. Where the two curves intersect is the perfect place to sell. This leads to better circular economy and, in the end, lower emissions. It’s better for everyone.”