How Analytics Empower Retail Fleets to Confront Operational Expenses

While inflation has been kept in check for much of the broader economy over the last few months and diesel prices have declined, the cost of diesel fuel may have negative ripple effects across the economy, particularly for retail fleets.

Demand for domestic transportation of goods is expected to increase in the coming months as retailers cut much of their excess inventory over the last few years and have focused on reshipping and restocking, along with construction projects spurred by President Biden’s stimulus plan that have led to an increase in the use of diesel trucks. This means diesel consumption will increase at a time when prices have crept back up and geopolitical tension has placed a further strain on diesel supplies.

The national on-highway average for trucking’s diesel fuel was $4.146 per gallon as of Nov. 27, according to the U.S. Energy Information Administration. While prices have fallen slightly over the last few months, a colder-than-normal winter may place even more pressure on supplies of diesel, making prices more difficult for retail fleets to absorb.

The trend is likely to place even more pressure on retail fleets operating on razor-thin margins at a time when overall costs are rising and they’re looking at every way possible to keep bottom lines healthy.

Costs Keep Rising for Retail Fleets

According to ATRI’s (American Transportation Research Institute) recent report, the cost of operating a truck in 2022 was $2.251 per mile, surpassing two dollars per mile for the first time in the history of ATRI’s studies. Sure, a lot of this increase was due to high fuel costs, but other cost centers saw jumps by double-digit percentages as well, including repair and maintenance, truck and trailer lease or purchase costs due to the increase in equipment costs, and driver wages.

The report also indicates that the cost of trucking, with fuel included, increased by 21.3 percent in 2022 compared to the previous year. Truck and trailer payments, repair and maintenance, auto liability insurance premiums, tires, and driver wages all set record high marginal costs in 2022.

On the private fleets side, the overall cost of trucking was listed as the third most prominent challenge in this year’s NPTC (National Private Truck Council) 2023 Benchmarking Report, compared with the fourth overall challenge the previous year.

All of this means retailers are now leveraging better data and analytics to pay closer attention to their truck replacement opportunities. Gone are the days of basing replacement decisions off experience-driven "guestimates." Today’s industry is centered on data technology driven by asset management firms that provide a holistic view to scrutinize how every individual spec impacts utilization and the bottom line.

As evidence of this, the December 2023 Truck Life Cycle Data Index (TLDI), calculating the cost savings associated with replacing older-model units with the latest truck equipment, shows that fleets can realize a first-year per-truck savings of $15,347 when upgrading from a 2019 model year daycab truck to a 2024 model. Across a fleet of 100 class-8 trucks, this equates to $1,534,700! This also represents a 12 percent decrease in emissions.

Maintenance and Repair Costs Escalating

Parts and labor cost data recently showed that significant cost challenges continued to impact retail fleets in 2023. According to data from American Trucking Associations’ Technology & Maintenance Council, on a year-over-year basis between the fourth quarter of 2022 and Q4 2021, parts and labor costs rose by 14.4 percent and 10.8 percent, respectively, and combined expenses were up 13 percent. Earlier in 2022, annual comparisons between quarters showed that combined parts and labor costs were up 15.3 percent, parts costs rose 15.8 percent, and labor expenses increased by 14.6 percent.

One way retail fleets are overcoming these cost challenges, especially for maintenance and bottom-line economic trends, is by leveraging predictive modeling. Predictive data leverages science and analytical trends to create algorithms and formulas that combine economic insights along with data mining trends to arrive at a forecasted output that's scrutinized for more accurate fleet planning.

When making critical business decisions, predictive modeling can be extremely beneficial in helping retail fleet executives leverage past and present data. These retailers have relied on data to leverage key insights to help determine a company’s TIPPING POINT, the point at which it makes more financial sense to replace an aging truck in the fleet with a newer, more efficient, and safer model.

Today, tech-savvy retailers are now using predictive modeling to help forecast this TIPPING POINT by looking into the future and selecting specific dates to gain visibility into life cycle performance and replacement economics of each truck. Fleets can analyze any number of criteria, including truck make, model and type, as well as utilization characteristics such as usage location and fuel metrics. This critical insight helps predict the savings over the next year, two years or three years and shows where unit replacements would present operational cost savings over the predicted time allotment during that time span.

With this data analytics technology, retail fleet executives can work with their asset management partners to identify where long-term cost savings can be found in the investment of newer trucks with safer technologies, even though the cost of equipment has increased on the front end. And with safety features more readily available on today’s new trucks, additional cost savings in accident avoidance and insurance can also be realized.

Comparing Cost of Diesel to Alternate Fuels

Lastly, with environmental regulations on the mind of many retail fleet executives, many are wondering when it makes the most sense to bridge over to alternate fuel technologies like electric vehicles. This bridge is different for every company, and data technology and analytic tools are now being utilized to help retail fleets take into consideration various inputs, including equipment cost, charging, cost of energy, cost of diesel, grants, tires, depreciation, etc., and converts them into a cost-per-mile to determine the total cost of operating an electric vehicle over its lifetime. Having this data allows retail fleets to make informed decisions about which type of vehicle is more cost effective for their fleet. In many cases, the data shows that diesel trucks are more cost effective for their operations, but now they have the data tools available to make the right comparison.

With the availability of the right data analytics, as well as strategic input from asset management partners, retail fleets are best equipped to make the right decisions to offset operational and diesel costs no matter the fluctuating price of fuel.

Katerina Jones is chief marketing officer for Fleet Advantage, a leading innovator in truck fleet business analytics, equipment financing and life cycle cost management.