Maintenance in the transportation and logistics space is primed for innovation. From diagnostics to creating a case and the actual repair work carried out by a technician, greater simplicity in the maintenance process and clarity around bottom-line impact should be the end result of technology.
Picking up since the electronic logging device (ELD) mandate in 2017 in the United States, the transportation and logistics industry has seen significant development and investment in new technology solutions. Maintenance, however, has typically been an afterthought — often seen as a technology area covered by existing systems or as a function of the business best regarded as a cost center.
Today, maintenance supervisors and technicians are piecing together information about their assets from a host of digital fleet management systems, whether that is enterprise asset management (EAM) software, computerized maintenance management software (CMMS), or general transportation software. In addition, many fleets collect and aggregate data from telematics, sensors, fluid samples, and fault code diagnostics in these or similar systems.
The result is that many shops are grappling with fragmented systems and noisy data. With telematics devices, for instance, maintenance tools are often included as a perk functionality. But there is not a single system to integrate these pieces as a whole.
Vehicles continue to roll in, data still streams, and fault codes are firing. Maintenance teams do not have the time or confidence to sift through all of their digital tools and data to get the direction they need to make sounder business decisions. The overload contributes to shops getting stuck in a cycle of reactive maintenance, with a slew of consequences across the board for fleet management dealing with routine and unanticipated repairs.
Most fleets have all the data they need to streamline better operational and maintenance decisions. The required data and subject matter expertise of technicians are on hand, just stuck in silos. With the aid of predictive analytics pulling data from telematics devices, sensors, fluids, and expert knowledge, maintenance teams can gain a more precise view of maintenance — reducing the number of insights by 90% while improving their impact on the bottom line.
For more information on how predictive analytics are helping fleets get more out of their data, download the white paper from Freightwaves and Uptake.
