Decisiv Announces Automatic VMRS Encoding Solution

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Cleveland — Decisiv has announced an automatic fleet encoding system using Vehicle Maintenance Reporting Standards.

The announcement was made on September 12th at the 2021 Technical Maintenance Council Autumn Conference and Transport Technology Exhibition of the American Trucking Associations.

VMRS Encoding for Fleets uses machine learning and artificial intelligence to analyze individual service operations, interpret the information captured during repair order creation, and assign the appropriate VMRS code to completed operations.

“VMRS coding is very valuable and can draw a lot of insights from the data when coding, but in reality it is at the service provider level and 15% of the service operations that occur across the platform are actually VMRS coded. “We are,” said Dick Hyatt, CEO of Decision. “It presents a challenge.”

TMC develops and licenses VMRS code to improve truck-related repairs.

“So we got structured data using this kind of cleansing tool,” says Hyatt. “So it’s now useful and valuable. It’s about what value we can offer and what insights we can provide here to our members, especially the fleet. It’s all about. “

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According to Decisiv, encoding is done independently after actual repair and maintenance work. In this way, fleets using Decisiv’s service relationship management solution can save time and money by eliminating the administrative work and costs required to manually apply VMRS code. The fleet has the option of receiving biweekly or monthly data in standardized files.

Decisiv said the new solution is further based on the partnership with TMC announced earlier this year. The partnership was formed to create a service event benchmark report that tracks key performance indicators based on the VMRS system.

VMRS encoding is also part of Decisiv’s new SRM Discovery family of analytics products and reporting services.

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https://www./articles/decisiv-unveils-automatic-vmrs-encoding-solution Decisiv Announces Automatic VMRS Encoding Solution

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