By Cheryl Garcia, Head of Global Freight Payment Relationship Management, U.S. Bank


(Note: This article previously ran in the American Trucking Associations’ Business of Trucking eNewsletter)


“In the business world, the rearview mirror is always clearer than the windshield.”—Warren Buffett


Looking back, how often do we find ourselves saying, “We should have seen that coming?” The clues were all there, if only we could have picked them out from all the other noise going on at the time. In other words, if only we’d seen the right data and been able to interpret it correctly.


We live in an age when everything from your vehicle to your wristwatch is generating data. It’s pouring into your reporting dashboard 24/7 from your GPS system, your fleet telematics, your mobile app and, of course, your fleet card. The U.S. Bank Voyager® Fleet Card, for one, records over 100 data elements that can inform driver and management decisions.


The challenge is to distinguish useful data—facts that when acted upon will achieve your specific goals—from the boundless stockpiles of merely interesting data that might be critical to someone else, but not you.


“I work with a lot of moving companies,” says Brandon Day, CEO of Daycos, a billing and invoicing service that assists carriers in submitting electronic invoices to U.S. Bank Freight Payment. “Ask any of them if they are using data in their business and 100% of them will say yes. But only a small number use it in a way that’s really helping them improve their business. It’s quite honestly hard to do.”


Day participated in a panel discussion on data moderated by U.S. Bank at a recent American Moving & Storage Association (AMSA) conference. The key to effective use of data, according to Day’s fellow panelist, IgniteMedia CEO Vladimir Collak, is to “start with your business objective and work backwards. What is your goal? What metrics do you need in order to know you’ve achieved it? What data do you need to gather to align around those metrics, and how do you find it? You have data everywhere. How do you compile it from all the various sources in a way that’s visible and useful for the organization?”


Getting the Right Data to the Right People, in the Right Format

Visible and useful go hand in hand, in that data can only be useful if it is visible—to the entire organization. It’s not enough that the executive team sees how the data measures against the metrics. All relevant parties need to see it, whether they oversee the board room or the bulk carrier.


“It’s hard for people on the ground to see beyond getting their next load delivered without knowledge of those metrics,” says Mansfield Oil Product Manager Zach Wall, a third member of the panel. “If they have visibility into how the whole organization is performing, it helps guide their actions towards greater efficiency.”


That’s one reason Daycos shares metrics relevant to company goals on TV monitors throughout its headquarters in Norfolk, Nebraska. At one time, the data was shared primarily amongst the Daycos leadership team, only occasionally extending beyond. “But we realized we were keeping that info basically to ourselves and not getting it to the people who can actually drive the numbers and change them,” says Day. “Now it’s in front of our employees 24/7 when they’re working. We’ve found it tremendously helpful in aligning the entire team around the metrics.”


Though it’s true that no data is useful without visibility, it’s also true that no visibility is useful unless the data reported is relevant and effectively presented. At one time, fleets and other transportation companies were happy to get any data at all. Now it’s about getting the right data at the right time, presented in a way that managers or drivers can take in at a glance and make good decisions with it.


Every organization is different, and no two organizations—even if they compete in the same industry—are likely to want the exact same data presented in the exact same way. Many third-party vendors specialize in helping organizations decide what’s important for them to know and then organizing data into a customized format. Some organizations are doing it on their own, using rapidly-developing new technology to aid the effort.


Real-Time Data

More and more, data is being synthesized in “real time” to inform decisions on-the-go. For example, if a diagnostic tool in a delivery vehicle warns of engine trouble, the driver can access the service station locator on the Voyager Mobile App to find nearest maintenance shop. The fleet manager, meanwhile, can use other tools to follow the driver’s route, make sure they find the shop, monitor how long the repair is taking and, if necessary, make arrangements for alternative delivery. In such scenarios, real time is critical. Tomorrow, that data loses much of its meaning.


“We use real-time data as the canary in the coal mine,” Day shares. “We’re looking to spot small problems before they become large problems. If we wait even two or three days before we spot it, depending on the time of year, thousands and thousands of transactions may be affected. If we can detect in real time, we can fix it—or at least not add to it till it can be fixed. It saves us a lot of time.”


Managing to the Exception

The sheer volume of real-time data now available, though, can be daunting to track. Our human computers (i.e., brains) can integrate many, many types of input in a given day, but the more they are asked to account for, the less granular they can get in making decisions.


One way around that is to “manage to exceptions” around what’s happening in real time. You can’t watch everything all the time, but you can set your profile to parameters that say, “I want to know when any of these operational parameters have been breached.” Then you can respond and ask, “Why did this happen right now and how can we fix it ASAP?”


Among the most promising benefits of real-time reporting is an enhanced ability to reduce the risk of fraud from stolen cards or driver misuse. By combining card swipe data with vehicle GPS data on the same dashboard, fleet managers would be able to spot when a card has been separated from its vehicle. If you see a card swipe at 2:40 p.m., but the GPS data shows the truck to be 50 miles away from any authorized fueling station, the manager would be alerted that something is up.


The caution in this scenario is the occasional occurrence of so-called “false positives.” Perhaps the payment location doesn’t match the GPS location because it reflects not where the fueling station is, but where the merchant processor is. Or perhaps the payment processor reports times in “batches” every half hour rather than real time. Though false positives can be an issue, technology is improving by the day and is likely to resolve it at some point.



Not all data needs to be, or should be, real time. Historical data renders perspective. It should, in fact, inform what you look for in the real-time data. It can be analyzed down to a granular level to quantify the financial impact of specific practices or procedures. For example, if vehicle data shows a driver consistently brakes too hard and re-accelerates too fast, the resulting decreased mileage and increased fuel spend can be calculated, then shared and used in driver coaching.


Real-time or not, granular or not, data holds the key to success and even survival in today’s (and tomorrow’s) competitive business landscape. As Wall put it, “If you aren’t using your data to the fullest extent possible to make your business more efficient, you can bet there’s a competitor who will figure out how to leverage it to make themselves more competitive.”


Analyzed correctly, the numbers don’t lie—use them. It’s the way to the clearest possible view at the road ahead and beyond.