All the telematics data streaming from commercial vehicles can be a double-edged sword, as they provide shops with real-time health monitoring and diagnostic trouble codes (DTCs) to improve efficiency and catch potentially critical issues, but can also overload them with the sheer amount of numbers a single vehicle generates.
How to combat this overload, and sort the critical information from less urgent, was a topic of discussion during a recent webinar presented by Pitstop, a provider of predictive fleet maintenance software, Samsara, which offers a diverse range of telematics and maintenance solutions. Speakers included CJ Ramsey, senior technical product marketing manager for Samsara; Rakean Zakir, customer success manager at Pitstop; and transportation industry consultant Jon White.
To begin, Ramsey pointed out how a good data management system is not only helpful, but necessary in the era of smart vehicles.
“If a vehicle has been driven for five days a week, the vehicle could potentially create somewhere between 2,500 to 3,000 diagnostic codes,” Zakir said. But somewhere between the thousands of DTC codes are the ones that can indicate an impending breakdown; shops only have to find them.
But having data management systems in place are not only critical for catching impending downtime, but for promoting uptime in the shop, too.
For instance, in the Society for Automotive Engineers (SAE) recommended practice J1939, “There are over 60,000 diagnostic trouble codes that are registered,” White said. “With that volume of data that can come in, the poor guy that's standing there in the shop trying to repair the piece of equipment and has got to look at diagnostic and repair codes has to have some support.”
Managing this massive influx of data, the webinar’s participants agreed, requires fleets to lean into the technology available to them. So, here are four features a fleet should look for when considering a data management service.
1. Data filtration and prioritization
One of the first aspects a fleet should look for when selecting a data management platform is the ability to filter their data depending on the fleet’s metrics and business goals.
"There's a lot of fault codes that show up that are just ghost codes," White pointed out. "If you look in the system today, there's a lot of WABCO [a U.S.-based braking, suspension, and transmission system provider] codes that don't even exist for components that are built."
Then a fleet's system needs to be able to prioritize their data depending on their need or risk, all of which depends on a fleet's profile.
"Not all maintenance events are created equal," Ramsey agreed. "We're able to leverage technology to help prioritize what gets put in front of us first."
Pitstop's platform does this by breaking down the data they collect into three categories, the company stated. These include ‘Critical Risk,’ which includes alerts for problems with a high likelihood of causing a breakdown; ‘Requires Attention,’ which means a problem does not put a vehicle at risk of imminent failure; and ‘Minor Alerts,’ which do not require immediate attention.
2. Wide applicability and security
However, a fleet management platform should not only be able to sort the data coming from a vehicle but also serve as a veritable archive of all the fault codes generated, regardless of whether a technician is specifically filtering for specific information or not.
Ramsey referred to this necessary feature as a ‘system of record.’
“A system of record just means that you are the authoritative data source for the organization,” Ramsey explained. “That's where all data is going into and where all data is coming out.”
For a platform to do this, it must be both reliable and secure, with the ability to provide consistent connectivity across the country, data security, encryption, and adherence to all compliance standards.
"Samsara was built on this idea of data security," Ramsey said. "Every piece of data going to our cloud and coming from our cloud is encrypted, both in motion and at rest. And we also maintain the highest compliance standards for [General Data Protection Regulation] in Europe, as well as the California data privacy laws here in the US, to ensure that you're not going to get hit by one of those nasty government fines for accidentally leaking somebody's data."
Plus, a system must be flexible enough to scale with a client and help a fleet know what they need to invest in to expand their business.
"Two years ago, we were collecting roughly 1 trillion data points a year, now we collect over 4 trillion data points per year," Ramsey commented. "The goal is that as you grow as a customer, we want to make sure that you have the necessary infrastructure to support that growth."
3. Integration opportunities
The webinar participants also stated that for a platform to consider itself a system of record, it needs to be truly comprehensive, which includes the flexibility to work with any partner system a fleet could use.
"We understand that we live in a time of change and a lot of our favorites OEMs and manufacturers are actually creating their own clouds," Ramsey admitted. "Chevy, Ford, GM, ThermoKing, all of them have their own, branded cloud dashboards that collect diagnostic information directly from the vehicle itself."
As such, a good fleet maintenance management platform needs to be able to collate all of a fleet's provided information into a single connected operations cloud.
“If you want to do everything through the same solid dashboard, that's fine,” Ramsey noted. “If you want to do everything through a third-party integration, like Pitstop, that's fine as well. Or, as most customers do, if you want to leverage some hybrid of both solutions, we can certainly accommodate that as well.”
This customization for platform interaction is particularly critical as many fleets may have one monitoring subscription already, if not more, whether for their tire pressure management or their aftertreatment system.
4. Customization and adaptability
Finally, a fleet data management system should respond to a business’s actual resources and adjust its maintenance recommendations accordingly. For Pitstop, this presents as a dynamic scheduling feature.
“This AI-based scheduling is able to take all of your telemetry information and our powerful insights and can recommend improvements in your PM cycle,” Zakir explained. “Our technology is able to learn from the equipment and the interaction that our system has with an existing work order management platform or manual interventions from front-line managers.”
All of these features are what allows a good data management system to efficiently triage maintenance workflow and includes factoring in several elements, such as the availability of parts, repair time, and whether or not a backup vehicle is available.
