When fleet managers examine their operational data, an important question is how it compares to similar fleets. Quarterly reports on national averages are not always precise enough to answer this question.
To that end, Penske Truck Leasing has announced a new platform to deliver real-time insight into fleet performance: Catalyst AI.
Penske’s Catalyst AI provides actionable data by comparing a fleet’s performance to similar fleets across Penske’s live database. This platform aims to provide fleet managers with greater actionable intelligence than traditional industry benchmarks, enabling leaders to benchmark their performance through apples-to-apples comparisons.
The need for relevant benchmarks
The new platform looks to fulfill fleets’ need for more relevant operational benchmarks. Fleets’ operational conditions vary widely, and it can be challenging to determine the average fuel efficiency or utilization for a particular operation.
“One of the things that they struggle with in our industry is a lot of the comparatives, a lot of the benchmarks are these aggregate measures that are not super timely—not very precise or accurate in terms of the exact fleet that they operate,” Sherry Sanger, EVP of strategy and marketing for Penske, told FleetOwner.
According to Penske, 77% of transportation professionals tend to rely on annual forecasting and industry benchmark reports to inform their decisions. This process can be manual and time-consuming—and may use data that doesn’t compare well to managers’ specific fleets.
Catalyst AI is a solution to this need: for metrics more comparable to a fleet’s unique conditions.
What Catalyst AI offers
The platform processes a large amount of other fleets’ data to find operating conditions similar to a customer’s. This processed data allows a customer to compare their own performance—for example, fuel efficiency—to those of similar fleets.
“What we’ve done is we’ve taken the vast volume of data that we have here at Penske, from running and operating hundreds of thousands of vehicles, and we’ve used that to create this data that our customers can use—to create their fleet DNA and create comparatives,” Sanger told FleetOwner. “Then they can use those comparatives to essentially identify opportunities for improvement.”
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Penske is able to launch this platform thanks, in part, to its wealth of operational data.
“We feel like we’re uniquely positioned because we have this large dataset, where we have customers that operate across different OEMs, different technology resources,” Sanger said. “We’ve got this really robust dataset that we can essentially help our customers collectively forward with.”
At launch, Catalyst AI currently offers insights into two key performance indicators: fuel efficiency and utilization. Customers will be able to look into the various drivers behind fuel efficiencies and improve their ability to maximize the use of their assets.
How does AI tie in?
Machine learning techniques help Penske process its large quantities of data for use in the Catalyst AI platform.
The dataset informing Catalyst AI includes about 57 billion data points, with 100 million data points added each day, Sanger told FleetOwner. Penske then uses several proprietary models, algorithms, and machine learning approaches to build a unique “fleet DNA.” This fleet DNA gauges multiple key dimensions to help classify comparable fleets.
A busy time for Penske
In addition to Catalyst AI, Penske has made two other major announcements in the last several weeks.
In mid-March, the company opened a new facility in Grand Rapids, Michigan, featuring five drive-through bays with 10 service areas, an automated wash bay, and a full-service fuel island. Later that month, Penske launched a large-scale electric truck charging pilot with Hitachi America and Hitachi Energy in the Stockton, California, area.
The company’s unveiling of Catalyst AI is its next major event for this year.
“It’s been an exciting year so far, and we’re excited about the announcement this week,” Sanger said. “We’re kind of just getting started this year.”
