“It’s not the technology that’s important, but what the technology enables us to do,” says Manpreet Rana, Vice President, Fleet Care and Logistics, Element Fleet Management.
“It’s helping us to get a vehicle back on the road more quickly, avoid unnecessary repairs, and supporting specialist mechanics to make better decisions.”
The technology in question is DigiAdvisor, which applies artificial intelligence to data from connected vehicles, and Element’s fleet management experience.
Smart beats size in fleet data
With a giant fleet of over 1 million vehicles in North America, Element is capturing data from 10,000 service and maintenance jobs every day. But it’s not the volume of this data that matters, so much as how it provides the foundation for better decision making by bringing the riches of this information together in one place.
DigiAdvisor mines Element’s data, connecting and cross-referencing it with vehicle telemetry, diagnostics, warranties and pricing to guide the decisions made by the company’s team of 150 ASE (Automotive Service Excellence) qualified mechanics.
“We are sitting on a huge, rich database, and when you combine it with telematics diagnostics it’s very powerful,” said Rana (pictured below).
Predictive maintenance
The system can identify, for example, that a particular make and model of vehicle operating in a specific geography typically needs new brake pads at a certain mileage. If one of these vehicles visits a workshop for other work, a few weeks before it reaches this mileage threshold, Element’s mechanics can discuss with their customers whether to change the brake pads as well, sacrificing a little wear for the larger saving of avoiding the downtime and business disruption of a second garage visit.
“Fleet operators are not struggling to access data. Their challenge is to turn fragmented information into timely, confident decisions,” said Rana.
He suggests that many people are asking the wrong questions about AI, wanting the technology to reduce costs, when a more fruitful question would be to ask how AI can support a smarter operating model.
Faster decision making
For Element, DigiAdvisor is enabling the earlier identification of potential issues. All fleet operators will be aware of how a missed maintenance issue led to unscheduled downtime, or how slow authorisation of maintenance jobs can keep a driver waiting and a vehicle off the road.
The new system is also accelerating decision making, spotting recurring maintenance problems, and supporting tighter control of warranty claims.
It finds links between connected vehicle data and maintenance events, enabling fleets to get on the front foot with predictive and preventative maintenance.
“It’s still early days, but we can already share that we can find the critical diagnostic codes from the telemetry and combine these with historical trends to show when work is needed,” said Rana.
The other side of the same coin means DigiAdvisor can identify which fault codes are benign, avoiding the cost of unnecessary repair work and vehicle downtime.
Warranty management
The IT solution also has an encyclopaedic knowledge of vehicle warranties, instantly understanding when maintenance work should be carried out under warranty, and saving mechanics hours spent reading the small print of manufacturer terms and conditions.
These mechanics have embraced the tool as a “co-pilot, not autopilot,” said Rana, because it frees them from mundane work authorisations and speeds up their decision-making process by minimising manual searches for information. This in turn creates more time to focus on complex cases and problem solving for clients.
“By turning fragmented information into clear, explainable and workflow-ready recommendations, DigiAdvisor helps our experts respond faster and more consistently, while keeping human judgment at the centre of every decision,” he said.
“DigiAdvisor spots things they could have missed – some customers’ fleet policies can be hundreds of pages long,” added Rana, highlighting how the system boosts compliance with fleet policies.
Human expertise vital
So, if a workshop sends in an estimate for maintenance work, DigiAdvisor will evaluate each line item of the job against the fleet’s policy, authorization limits, pricing rules, outstanding warranty cover, and previous repairs. The technology will then present its recommended course of action (approve, negotiate, reject) to Element’s mechanic, alongside the grounds for its verdict.
Routine fixes that are within the fleet’s policies and authorization limits can be automatically sanctioned.
“But if the mechanics disagree with the AI verdict, we investigate the disagreement. It’s part of the challenge of harnessing AI without losing human expertise,” said Rana.
Vehicle connectivity
About 35% of Element’s fleet is currently connected, either by OEM-embedded systems or third-party telematics suppliers, and the percentage is rising rapidly as more vehicles leave the factory line with connectivity features.
“Our target is to get to 100% connected,” said Rana.
The return on investment in terms of improved uptime and reduced maintenance spend comfortably offsets OEM subscription fees for accessing connectivity data, he added.
Moreover, DigiAdvisor’s insights will also feed into remarketing decisions, identifying which vehicles to sell and when to sell them to avoid escalating maintenance spend.
“Every better maintenance decision means higher vehicle uptime, lower operating costs and a better experience for our clients,” said Rana.
Image: Shutterstock_2778804195