The bumpy road to maintenance data standardization

The road can be bumpy for any company rolling out operational changes. Adapting people to something new means earning their buy-in, adjusting policy and procedures, and managing any gaps or overlaps in the transition.

Here’s a sample fleet situation to demonstrate this: you’ve decided to roll out a new vehicle maintenance program. Some bumps might include initial compliance with preventive maintenance schedules, adapting to changes in the vendor network, and managing purchase order payment issues. Don’t take the first exit—there are ways to navigate this potentially rough road!

Starting fresh with a fleet management provider that offers robust data capture and analysis capabilities means you’re now gaining valuable data from your vehicles, drivers and vendors. The faster you can gain insight on how your vehicles are operating and performing, the more confidence you will gain with making fleet management decisions.

Wiping the dust off historic data

Let’s discuss a real-life fleet scenario: a new ARI client recently rolled out our maintenance management program and Garage Management System to 2,200 light-, medium-, and heavy-duty trucks, equipment and trailers. The client’s sizable fleet was well established, so maintenance records on the vehicles did exist in some form. To make a start, ARI worked with the client to capture and upload loose historical vehicle information from prior to the launch of ARI’s maintenance program.

Once a company is utilizing our fleet management programs, we usually recommend collecting 12 full months of stable data before making any major decisions, but after six months on ARI’s maintenance solutions, the client was eager to start looking at trends. Although the client’s historical maintenance data was spotty at best, we jumped right into establishing a baseline and the framework that would be filled with the client’s incoming data moving forward.

Filling the data holes

Digging deeper into the archives, we uncovered a significant hole in the client’s data: the historical maintenance records only included active vehicles.

This analysis also demonstrated the effectiveness of the client’s choice to “repave” their fleet management approach with ARI. Soon, the client was using our systems to consolidate outsourced maintenance data with data generated from their in-house maintenance garages—and standardizing their data using 80 ATA group codes and 4,276 additional 8-digit ATA codes. Each code represents a specific part on a vehicle that is universally known within shops and OEMs, and will highlight expense trends essential to future analyses.

Smooth road ahead

The client has other areas of maintenance opportunities as a result of this preliminary data exercise:

  • Optimal replacement cycling – to stabilize acquisition and maintenance expenses while sustaining healthy vehicles in the fleet.
  • Preventive maintenance policy – to improve compliance, appropriate scheduling and vendor selection.
  • 12-month maintenance trends and primary cost contributors – to identify the prevailing trends and “pain points.”
  • Garage analysis – to quantify what type of repairs are being done in-house vs outsourced and if there is an opportunity to improve the effectiveness of the garage

The ongoing data stabilization will empower the client to leverage predictive analytics and make fleet decisions that will help drive the company’s overall success down a much smoother road.

Sure up your data – Sure up your fleet spend

Your fleet data is critical for spotting trends, implementing changes, and affirming improvements. For this company, adopting our maintenance management program was an eye-opener as to the value of fleet data for knowing how much you’re spending and what you’re spending it on, in order to gain control over unnecessary costs.