Business Intelligence Creates Profits for Commercial Truck Fleets

Editor’s note: Written by Brian Holland, president and chief financial officer at Fleet Advantage, a truck fleet business analytics, equipment financing and lifecycle cost management analysis firm. This is one in a series of periodic guest columns by industry thought leaders.

Almost every industry today is utilizing big data in some fashion, and this is a growing strategy for organizations that utilize heavy-duty trucks in their fleet. Big data is typically defined by large volumes of unstructured, raw data. Its sheer size can overwhelm organizations.

How to interpret the data and put it to use is where commercial truck fleets often struggle.

brian-holland

Brian Holland

While commercial truck fleets can competently operate hundreds to thousands of vehicles, collecting and interpreting truck data is still a new process for many. Fleets typically lack the tools and resources needed to properly monitor and analyze the volume of data they receive to make critical decisions that reduce their total cost of vehicle ownership, or TCO. What’s worse, some organizations can’t leverage the data that they do collect. According to a recent Fleet Advantage survey, fleets are working to utilize big data. But 33 percent of fleet executives said they don’t have a software platform that allows them to manage their fleet’s TCO all in one place.

Once companies with commercial truck fleets begin to leverage data and implement proper asset management software, they can hone their operational strategies, procurement, truck maintenance practices and more.

The future of transportation fleets is centered around business intelligence. Procurement, operations, financial decisions and logistics are all based on platforms that leverage, catalog and analyze the data, offering a distinct competitive advantage. Fleet executives need a system that aggregates and consolidates their truck operating data along with multiple third-party data into one platform. That will allow them to generate sophisticated business intelligence and fleet data analytics to make more efficient, timely and profit-maximizing decisions.

Today’s leading companies and their suppliers are employing asset lifecycle management and technology resources that can help them to make more strategic and profitable decisions that affect their bottom line. This enables a more simplified and intuitive view of information most pertinent to their operation: maintenance and repair data, fuel economy, vehicle performance and utilization, replacement vehicle savings and finance costs.

There is no one factor that has a greater impact on total cost of ownership in managing the asset’s lifecycle. Many companies operate on legacy philosophies that now must adjust the advent of data, analytics and telematics. Executive-level decision makers are now realizing the power of data, and how it is shaping their business and financial decisions for the long-term competitive future of their organizations. For instance, Navistar, the owner of the International line of trucks, uses geofencing to learn how long it takes for a service center to repair a client’s truck.

The most prominent example of this evolution can be seen at the asset acquisition strategy level. Many companies with private fleets and for-hire carriers no longer are wed to long-term truck ownership. Business Intelligence is proving that shorter asset lifecycle implementation is the future of the industry.

The most powerful business intelligence marries the fleet’s necessary financial and operating data together for a complete look into the asset’s lifecycle.

For example, asset management tools available to transportation fleets can monitor the usage of equipment, which plays a critical role in not only the acquisition of equipment, but also in identifying the optimum time to replace aging equipment. Below is an example which shows the breakdown of a fleet by model year (MY) [blue bars] along with the maintenance cost per mile [red line].  Theoretically, since older trucks have higher maintenance costs, this fleet should consider upgrading the eighty 2014 and 2015 MY vehicles to optimize their lifecycle and achieve significant cost savings.

Commercial truck fleets are adopting shorter asset lifecycle strategies by leveraging flexible lease programs driven by data analytics that identify the point at which it costs more to operate an aging vehicle compared with the cost to replace it with a new truck. Factors such as monthly payment, interest, depreciation, the cost of fuel, and utilization all play a role in factoring maintenance and repair costs. Utilizing data algorithms, both operations personnel and finance departments have a closer look at their fleet organization and how it affects their overall business.

A large fleet would be hard-pressed after a thorough review and revamping of processes, labor costs, parts costs, etc. to reduce their maintenance and repair costs by greater than 5 percent to 7 percent annually. Likewise, they would be equally challenged to improve fuel economy by as much as 2 percent to 3 percent annually. Exchanging old equipment for new trucks at approximately four years or 400,000 miles for over-the-road class-8 tractors offers the most considerable leverage for cost reduction.

Every transportation fleet today does their best to reduce costs and increase efficiencies, and although these are essential to cost management, they are just the beginning when compared to asset lifecycle management.

Editor’s Note: Brian Holland is president and chief financial officer at Fleet Advantage, a truck fleet business analytics, equipment financing and lifecycle cost management analysis firm. 


Trucks.com welcomes divergent thoughts and opinions on transport technology and trucking industry issues. Use the comments section to cite yours. Qualified opinion leaders are welcome to offer suggestions for opinion columns. Contact info@trucks.com

Jerry Hirsch August 21, 2019
Daimler Trucks delivered the first of its electric Freightliner eCascadia Class 8 trucks to Penske and NFI.

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