November 14, 2016

Fleet Advantage Releases Q3, 2016 Truck Lifecycle Data Index

Q3 Data Shows Continued Per Truck Cost Savings Increase For Year-One Replacements

Fleet Advantage, a leading innovator in truck fleet business analytics, equipment financing and lifecycle cost management made public today its third quarter, 2016, Truck Lifecycle Data Index (TLDI) comparing all-in operating costs of early-model Class-8 trucks to all-in operating costs of current model year replacements.  The TLDI shows fleet operators the cost savings involved when replacing older-model vehicles with 2017 trucks. In fact, these replacement numbers show a slight increase in savings (roughly 2%) over the replacement comparisons during the second quarter.

According to Fleet Advantage’s ATLAAS (Advanced Truck Lifecycle Administrative Analytics Software), the TLDI from third-quarter data shows that fleet operators can realize a first-year per-truck savings of $19,023 when they upgrade from a 2011 model-year truck to a 2017 model. These comparison numbers are critical in helping fleet operators recognize each vehicle’s “tipping point” – the point at which a truck reaches economic obsolescence, and costs more to operate than to replace with newer equipment.

“As fleet managers begin to budget for 2017, it’s important they understand the cost savings involved with replacing trucks more frequently to maximize savings,” said Kenneth Loricchio, Manager of Advanced Analytics. “Regardless of the price of diesel, the Greenhouse Gas Mandates make frequent upgrading to new equipment result in a more fuel efficient and cost effective operation, particularly when maintenance costs of older vehicles are factored in.”

Fleet Advantage offers valuable information for truck fleet operators including financial and valuation insights required for maximum value and use of asset.  Data analytics from ATLAAS including the Truck Lifecycle Data Index help truck fleet operators save millions of dollars annually for companies replacing older vehicles and opting to adjusting lifecycle practices to a data-driven model.

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