There is so much enthusiastic talk about the value of big data these days that it sometimes sounds almost magical in its ability to transform fleet operations and turn losses into profits. While using data analysis is certainly not as easy as waving a wand, it can make invisible realities suddenly visible for fleets and put isolated information into relevant and revealing context—and that really can make a difference to the bottom line.
Mike Hamilton, senior vice president of financial services at Ameriquest Transportation Services, recently talked with Fleet Owner about how Ameriquest is now using data analysis to help fleets find significant cost savings, "hidden in plain sight” in their data. No wonder the company has grown by 52% over the past three years and been on Inc magazine’s fastest growing companies list seven times
“When Ameriquest was founded back in 1996, most people knew us as a parts procurement company,” Hamilton said. “We still do that, but today the company is really so different; it is actually a business process outsourcing company now. We are kind of a sleeper, just quietly going about our business of trying to save our customers money.”
According to Hamilton, today the company has about 700,000 vehicles in more than 1,500 companies under its management. To accomplish that, it is divided into three major areas: Supply Management, including procurement, group sourcing and spend management; Managed Services, including financial, equipment remarketing, National Lease, and credit and collection; and Financial Processes, including accounts payable. These various perspectives give Ameriquest views through many different data windows and what they discover for fleets can be surprising.
“We are going in and looking at how fleets are operating now,” Hamilton told Fleet Owner. “For example, we have a large customer that has leased from others in the past. We went in and said, ‘You’ve never given anybody all your maintenance and fuel data. Let us take a look.’”
After doing some analysis, Hamilton said they determined that the carrier was “running equipment about one year too long” and that shortening the trade cycle could save about $1 million over the lease term. “There is value in obtaining that data for customers,” he noted.
In another case, Hamilton said that the company was able to find cost savings for a fleet customer by individualizing replacement schedules for each vehicle rather than trading all equipment at a fixed mileage point. “One of our private fleet customers has been using a replacement model to accurately project mileage and making their decision on replacing tractors at about 550,000 miles,” he said.
“We obtained all of the historical maintenance and repair data, utilization and fuel economy data and have been able to provide them with a more complete database that allows us to include their actual maintenance and repair cost and historical fuel performance on each specific unit. The new process allows them to make a decision to replace a unit or extend the use of a unit for a few more months. When maintenance costs and fuel were included in their replacement decision in addition to utilization, we uncovered an additional $600,000 that they were able to save by replacing units at exactly the right time. That’s real life-cycle optimization!”
Asking the right questions turns out to be supremely useful when you are looking at data, Hamilton said. Questions like ‘Do you know what you are spending on tires now? Do you know why you are going through so many air conditioners? Has your fuel economy changed over time on this lane, with this truck?’ can lead to big cost reductions.
“Right now I am in the process of helping a fleet reduce the number of tractors they require by ten percent,” Hamilton said. “We are not in the business of trying to lease people more equipment.
“We get really passionate about the data because it is so powerful,” Hamilton observed. “We can do so much with it. Data analysis can help mid-market companies stay competitive.”
