Need to Cut Last Mile Delivery Costs? These Are the Key Areas

Scaling your last-mile capacity to match increasing online order volume while simultaneously meeting rising customer experience expectations and higher costs is hard. For many retailers, that's also reality. It's today's version of the old cost-quality-time conundrum: "Do you want it good, fast, or cheap — pick two."With last-mile costs making up 41% of all logistics spending worldwide according to a Capgemini Institute study, this isn't just your problem. It's an industry wide issue that has a major impact on consumers (who ultimately pay for shipping), on manufacturers who make the goods, on transport companies including 3PLs, on the environment that absorbs the carbon generated by shipping, and of course on retailers — who are the last stop before the last mile. 

The key to overcoming these challenges is to first understand the scope of the problem by analyzing the component costs of your particular last mile and then finding the right technology to address them. 

Analyzing Costs in the Last Mile

Not all of the cost drivers are obvious, but the major ones are well known:

• Labor — the supply of drivers is still constricted, while driver pay continues to climb 
• Fuel and fleet maintenance
• Warehousing
• Reverse logistics
• Technology

Customers want the convenience of having items dropped at their doorstep. Multiple studies confirm that between two-thirds and three-fourths of online shoppers say the quality of the delivery experience affects their choice of retailers and whether they are willing to buy from a retailer again. 

Maintaining the quality of the delivery experience helps build brand, but it also costs money. 

All of this adds up to one important fact: logistics optimization to manage costs is non-negotiable. 

The Top 5 Sources Last Mile Delivery Costs

Labor costs

According to the U.S. Bureau of Labor Statistics, hourly pay for drivers is highly dependent on location. In 2023 the mean pay (half of drivers earn less and half earn more) in rural Alaska was $28.12 hourly, $25.72 in San Francisco but only $17.55 in coastal North Carolina. Nationally, UPS averages $23.35 per hour. Statistics from the National Transportation Institute show that per-mile driver pay grew 6% in 2023 alone.

These increases are likely to continue in the near to mid-term future, so minimizing the labor required to make a delivery is critical to managing labor costs.

While the market price of labor is out of your control, how you use that labor is very much controllable. The number to focus on is the labor cost per delivery, and increasing the number of deliveries your drivers make in each shift through optimization can lower your overall labor costs despite increases in hourly pay. 

Reducing fuel use in the last mile 

Fuel costs are both significant and unpredictable: In the U.S., the national average price of a gallon of diesel ranged from a high of $4.63 to a low of $3.66 during the most recent 12 months, a swing of 25%. Booming oil production inside the U.S. — which is now 20% of all production globally and leads all oil-producing nations — coupled with increased production in Canada, Guyana, Brazil and Norway helped drive down prices that spiked amid the pandemic era production crash and Russia's invasion of Ukraine. However, continued global instability and weather events that affect supply and distribution can push prices up significantly with little or no warning. 

There's also the matter of sustainability: Consumers continue to show preference for brands working to minimize their environmental impact. While packaging does contribute to the environmental costs of logistics — and there's been an upsurge in alternative packaging to address those — fuel is still the largest contributor of carbon in the last mile. 

For managers, both of these underscore the importance of minimizing fuel use. The way to do that is by reducing miles driven per delivery. Optimization plays its role here in two ways: Making the most of fleet capacity so that trucks don't depart the dock half–full and cutting unnecessary miles. 

If you're using the pen-and-paper method of routing or a simplistic shortest point-to-point solution, you won't get there. Because there are so many variables that affect delivery routes, compared to older solutions, AI-enabled routing coupled with machine learning (ML) is essential. Routing software with AI and ML actually gets more accurate and efficient as it gathers data from completed routes. 

This intelligent optimization has proven to reduce miles driven by 10%. That's 10% less fuel consumed. The impact of that goes far beyond the pump, too. That's making the same number of deliveries with fewer service units, lower maintenance costs and fewer driver hours too. Plus, you'll reduce the amount of carbon emitted by your fleet.