Ultimate Guide to Last-Mile Delivery Costs
Introduction to Last-Mile Logistics Costs
Last-mile logistics refers to the final stage of the delivery process, where goods move from a distribution center or transportation hub to their ultimate destination, typically a customer's doorstep. This crucial segment involves intricate planning and execution to ensure timely, efficient, and cost-effective delivery.
Last-mile logistics holds immense significance in the modern business landscape. It directly impacts customer satisfaction and loyalty, with studies revealing that three-fourths of customers express a willingness to spend more and remain loyal to brands that offer an exemplary last-mile experience. Furthermore, it's pivotal in determining overall shipping costs, constituting a substantial 53% of the total shipping expenses. Notably, it accounts for a staggering 41% of all supply chain costs globally.
The complexities within last-mile logistics are multifaceted. Costs vary significantly based on package size, destination density, and delivery location. For instance, the average cost per delivery for a small package to a high-density area stands at $10, while delivering a larger package to a low-density area escalates the average cost to $50. Failure to optimize delivery costs amidst surging online sales could lead to a substantial 26% decline in profits over three years.
A comprehensive understanding of last-mile logistics costs highlights its immense financial impact. However, it's not just about expenditure; it's also a critical determinant of profitability. Illustratively, an increase in online sales without optimizing delivery costs could significantly impact profitability.
The classic segmentation of the freight transport market, as illustrated in the figure below from the paper "Home Delivery and the Impacts on Urban Freight Transport" delineates home delivery as a key domain of mail and parcel operators, as well as courier services.
Direct Costs
Labor Cost
The economic cost of last-mile delivery is heavily influenced by labor expenses, which exhibit significant variability based on location and service type. In the United States, delivery truck drivers earn an average hourly rate of $15.12, while local delivery couriers command approximately $16.74 per hour. Express delivery teams charge a higher rate, averaging around $25.10 per hour. Similarly, in France, “chauffeur livreur” positions range from €21,356 to €29,279 annually, equating to approximately €12.36 per hour.
The relationship between labor costs and delivery time is pivotal, yet delivery times are subject to significant variability. Factors such as traffic congestion, road closures, adverse weather conditions, and other unforeseen circumstances can markedly impact the efficiency of last-mile delivery services. This unpredictability poses challenges, affecting delivery reliability, potentially leading to increased labor hours, and consequently, higher costs.
Furthermore, the nature of the delivery, whether it necessitates recipient interaction, signatures, or complex setups, adds to the unpredictability. Such requirements beyond the purview of the local courier can disrupt scheduled deliveries, potentially inflating labor costs.
Moreover, the recipient's location significantly influences delivery efficiency. While meeting delivery promises is not location-dependent, logistical challenges vary. Deliveries to areas near distribution centers or accessible suburban locations tend to align more reliably with schedules. In contrast, deliveries to rural or highly congested urban areas pose greater logistical hurdles, potentially contributing to increased labor costs and operational challenges. These factors underscore the intricate interplay between labor costs and the uncertainties intrinsic to last-mile delivery, necessitating efficient logistical strategies to manage economic burdens while ensuring timely and reliable services.
Fuel Cost
The economic implications of last-mile delivery are evident, especially concerning fuel costs. Approximately 10% of last-mile delivery expenses account for the fuel bill alone, a seemingly modest percentage that significantly impacts businesses. For instance, Amazon's adjustment of prime membership prices from $99 to $119 in 2018 reflects the direct consequence of rising fuel expenses, underscoring how such costs affect consumer prices.
Understanding fuel price calculations reveals a complex interplay of factors, including taxes, oil costs, and transportation and distribution expenses. In France, for instance, taxes contribute to about 56% of the fuel price, while the cost of oil makes up approximately 35%. This breakdown emphasizes the multifaceted nature of fuel pricing.
Idling, a common occurrence in city driving during last-mile delivery, substantially affects fuel consumption. Delivery trucks idle at an average rate of 0.84 gallons per hour, significantly contributing to increased fuel usage over time. This idle time accumulates due to factors like traffic congestion and frequent stops.
Moreover, out-of-route miles pose another economic challenge. Drivers often deviate from planned routes, accounting for about 10% of the delivery fleet's total mileage. These deviations lead to increased fuel consumption and labor costs, highlighting inefficiencies within the delivery system.
Considering the variety of fuels authorized in France, in compliance with EU directives, there's an ongoing effort to diversify options and promote alternative fuels such as electricity, hydrogen, and ethanol blends. EU directives like 2014/94 aim to expand infrastructure for alternative fuels, fostering a more diverse and sustainable fuel landscape.
The economic impact of last-mile delivery becomes apparent through the intricate dynamics of fuel costs, inefficiencies like idling and out-of-route miles, and the ongoing efforts to diversify fuel options. These factors collectively emphasize the need for innovative solutions to mitigate economic burdens while aligning with ecological sustainability.
For real-time monitoring of fuel prices across different regions and cities in France, the government's official website, prix-carburants.gouv.fr , provides comprehensive data. Mandated by ministerial decree, this site obligates fuel retailers who have sold at least 500 cubic meters of SP95, diesel, E85, GPLC, SP95-E10, or SP98 fuels to declare their prices. Non-compliance with this obligation can result in fines, with price controls conducted by the DGCCRF.
The "Décomposition des prix des carburants" is an illustrative chart displaying a breakdown of costs associated with two primary fuels: SP95 and gazole (diesel). Presented in bar chart format, it delineates the percentage distribution of various components contributing to the overall price of these fuels. These components typically include taxes, oil costs, transportation, distribution, and other associated expenses. The visual representation aims to highlight the proportionate contribution of each factor to the final retail price of SP95 and gazole.
Delivery Equipment Cost
Delivery equipment costs account for a substantial portion of last-mile delivery expenses, requiring the right vehicle for safe and efficient product transport. Several factors play a crucial role in selecting an appropriate delivery vehicle:
This chart compares the financial aspects of outright purchase versus full maintenance contract hire for vehicle ownership over different periods—2, 3, and 4 years.
The conclusion drawn from the comparison indicates that contract hire and long-term rental outperform outright vehicle purchase, even when adjusting the discounted cash flow (DCF) rate from 15% to a more realistic 10%. There's no allowance for borrowing costs in the purchase figures, which further favors vehicle hire financially, particularly if a loan is needed for vehicle purchase.
While DCF is crucial in evaluating vehicle purchase costs, it's advised to thoroughly explore available hire options, considering their benefits and potential investment opportunities.
Packaging
The prices that the producers provide gives us an estimated cost for different types of custom packaging across varying production run sizes. Key details are broken down for folding cartons, corrugated boxes, rigid set-up boxes, flexible packaging, and blister packaging.
For each category, pricing information is shown for prototype and short to large production runs. The data clearly shows how volume impacts per unit pricing substantially. While prototypes may cost $5-10 each for example, large production runs over 50k+ units can cost under $0.20 each.
Tooling and Setup Costs An important aspect is the differentiation between tooling/setup costs and per unit costs at different volumes. Prototypes often involve no tooling investment, with simple production costs driving the high per unit pricing. However, short to large production runs require investing in custom tooling, such as cutting dies for folding cartons or production machinery for blister packaging.
This tooling investment ranges widely, from a few hundred dollars for some boxes to several thousand for rigid boxes and blister packs. The benefit is dramatically lower per unit pricing once volume distributions absorb the tooling investment. Optimizing this tradeoff is a major factor in packaging decisions.
Economies of Scale The data clearly illustrates the economies of scale at work. Across all packaging types, per unit cost drops dramatically between short runs of 1,000 units to mid-sized runs of 5,000-25,000 units, often by over 50%. Per unit costs continue to decrease, albeit less aggressively, as volumes increase towards 100,000+ units.
This scale economy is especially evident in flexible packaging and blister packs, likely due to their more complex production processes. Mid-sized runs of 25,000+ units can cost 60-75% less per unit compared to short runs. This factor, along with upfront tooling investments, creates high barriers to entry for custom packaging without substantial volumes.
This table summarizes the tooling costs and cost per unit across different quantity ranges for each type of packaging. The data provides quantifiable estimates on how custom packaging costs are heavily dependent on product volumes, tooling/setup costs, and the economies of scale at different production runs. This can support strategic decision-making when considering investing in custom vs. generic packaging.
Maintenance
In the realm of urban delivery, the cost of maintaining a fleet of vehicles stands as a notable challenge, encompassing various aspects that significantly impact operational expenses. Embracing fleet ownership necessitates shouldering the entirety of maintenance expenses, which span routine preventive tasks like oil changes, tire rotations, brake examinations, and the unpredictable realm of unexpected repairs. Beyond the upkeep, meticulous records of each vehicle's maintenance history must be meticulously preserved, ensuring a timely completion of all maintenance tasks.
The critical metric of fleet maintenance cost per car remains pivotal, encapsulating the total expenditure involved in preserving vehicles at their optimal functionality, thereby forestalling unnecessary breakdowns. This metric, however, fluctuates contingent on multifaceted determinants: the vehicle's age, type, usage patterns, size, as well as the caliber and frequency of repair interventions. Moreover, this figure inherently intertwines with industry-specific wear and tear expectations, notably divergent across sectors such as construction or cross-country cargo delivery.
To precisely gauge the cost intricacies within a fleet operation on a per-car basis, leveraging the Total Cost of Ownership (TCO) method serves as a comprehensive approach. This methodology entails amalgamating both fixed and variable costs inherent in owning and operating a vehicle across its lifespan. Encompassing facets like acquisition, depreciation, fuel, insurance, taxes, repairs, and maintenance, TCO encapsulates the holistic panorama of expenses attached to fleet management.
Delving deeper into the intricacies, various cost elements emerge as significant contributors to the overall operational expenditure of urban delivery fleets. Considerations such as truck or trailer lease or purchase payments, truck insurance costs, depreciation rates tied intricately to maintenance diligence, and the labyrinth of licenses and permits, each hold sway in shaping the financial landscape of fleet management. These elements, in conjunction with the holistic TCO framework, facilitate a nuanced understanding of the fiscal demands posed by fleet ownership and operation.
To conduct a comprehensive fleet management cost analysis, a pivotal step involves calculating the total cost of ownership per vehicle, employing the straightforward equation: TCO equals the sum of fixed and variable costs. This calculation lays the groundwork for determining the vehicle cost per mile by dividing the TCO by the cumulative miles traversed.
Armed with this quantified comprehension, data-driven decisions come to the forefront, facilitating enhancements in operational efficiency. Choices regarding vehicle retention, expansion, or reduction of the fleet size, tailored preventive maintenance strategies, contemplation over leasing versus purchasing vehicles, and an in-depth evaluation of driver behavior and performance are bolstered by this analytical framework.
The breadth of necessary documentation in the realm of urban delivery operations extends beyond the vehicles themselves. A repertoire of essential papers, encompassing vehicle-specific documents to those pertaining to the transported goods, stands as indispensable requisites for ensuring compliance, safety, and operational legality in the urban delivery landscape.
For independent contract drivers engaged in rideshare and delivery services, the burgeoning expenses entwined with vehicle repair and maintenance form a substantial aspect of their operational overheads. The escalation in these costs has been stark, surpassing 11% over the past year (2022), a marked contrast to the consistent 4%-5% annual increments witnessed in prior years. Notably, the driving patterns of such drivers differ significantly from average U.S. drivers, with weekly mileage often surpassing 1,000 miles, a stark contrast to the 14,263 miles recorded annually for the average U.S. driver by the United States Department of Transportation – Federal Highway Administration (FHWA) in 2019. This higher mileage directly correlates with amplified vehicle repair and maintenance expenses, as delineated in a chart showcasing annual costs. The spectrum varies widely, from approximately $1,470 for a small sedan covering over 15,000 miles annually to a substantial $6,111 for a medium SUV navigating through 55,000 miles annually.
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Delivery Management Software costs
The integration of delivery management software stands as a crucial aspect within last-mile logistics, constituting approximately 10 percent of the overall expenditure involved in last-mile delivery operations. However, the cost intricacies surrounding this software are multifaceted and contingent upon various factors. On average, the pricing for delivery management software hovers around $182.35 per month. Yet, this figure fluctuates significantly across different providers, each offering distinct subscription models and billing methods, making it a complex decision for businesses. For instance, upon analyzing a scenario involving a business operating five vehicles and completing 1000 deliveries monthly, a comparative study of several market-leading delivery management software reveals varying subscription costs: Onfleet and Route4me at $149.00/month, eLogii and Tookan at $159.00/month, Optimoroute at $175.50/month, and Routific at $195.00/month. However, the divergence extends beyond mere pricing, as providers offer different feature sets, billing methodologies (per delivery, per vehicle, per driver), and subscription models, thereby complicating the decision-making process for businesses seeking an optimal solution.
External Costs
Road Traffic Accidents and Associated Costs
Road traffic crashes constitute a substantial economic burden and a significant public health concern in France. As of 2020, the economic impact of these accidents was estimated to be approximately EUR 37.9 billion, accounting for 1.6% of the nation's Gross Domestic Product (GDP). However, according to the findings of the VALOR1 project, the extrapolated cost of road traffic crashes reached a staggering EUR 77.8 billion in 2019, highlighting the magnitude of this issue within the country's economic framework.
In terms of fatalities, the recorded data indicated a total of 2,541 deaths resulting from road traffic accidents. The distribution of fatalities among different categories of road users unveils a concerning trend. Car occupants accounted for the largest share at 49%, followed by motorcyclists at 23%, pedestrians at 15%, cyclists at 7%, and the remaining 6% categorized as 'others.'
Furthermore, examining the mortality rates per demographic parameter reveals pivotal statistics. The rate of road fatalities per 100,000 population stood at 3.9, while per 10,000 vehicles, the rate measured 0.5 fatalities. These figures underscore the pressing nature of road safety concerns within the French context, showcasing the severity of the impact on both individuals and vehicular assets.
The economic repercussions of these accidents extend beyond the immediate loss of life and include a significant financial burden. The estimated cost of road crashes, amounting to approximately 1.6% of the national GDP, emphasizes the substantial economic toll incurred by such incidents.
This academic exploration of road traffic accidents in France underscores the multifaceted challenges they present, encompassing not only human lives lost but also substantial economic implications. The need for comprehensive strategies and interventions to mitigate these impacts and enhance road safety remains a critical imperative for policymakers and stakeholders within the country.
The figure below illustrates the 20-year evolution (2000-2020) of road fatalities, injury crashes, motorization, traffic, and GDP in France.
Environmental Noise
Environmental noise poses significant social costs across the European Union (EU), amounting to approximately 40 billion euros annually. This substantial figure primarily stems from road traffic, specifically passenger cars and heavy vehicles, contributing to 90% of the total noise-related expenses. Remarkably, these costs represent around 0.4% of the entire EU GDP, underscoring the economic impact of environmental noise.
In understanding the effects of noise, it's acknowledged that there exists a non-zero threshold level. Below this threshold, most individuals are not significantly annoyed, whereas above it, most experience annoyance. However, it's crucial to note that the threshold varies among individuals and locations. The Organization for Economic Cooperation and Development (OECD) emphasizes this variability, highlighting that the threshold sits around 55 dB according to literature reviews.
The presented table analyzes the marginal costs of noise resulting from a 10% increase in vehicle-miles of travel (VMT) for various vehicle types across diverse road categories in urban areas. It showcases substantial variations in noise costs across road types and vehicle classifications.
Different vehicle types exhibit varying noise costs across road categories. Heavy-duty trucks consistently demonstrate higher noise costs across all road types compared to other vehicles. Major roads such as Interstate Freeways and Principal Arterials generally exhibit higher noise costs, indicating potentially heightened noise impacts on these roadways.
The scenarios—base, low-cost, and high-cost—illustrate varied noise cost implications. The base case suggests potentially higher noise impacts from vehicular traffic, while the low-cost scenario indicates reduced noise impacts. Conversely, the high-cost case portrays increased noise impacts or higher sensitivity to noise levels.
This data provides crucial insights for urban planners, policymakers, and transportation authorities to develop targeted strategies to mitigate noise pollution in urban areas. Understanding the nuanced impact of vehicle types and road classifications on noise costs is pivotal in formulating interventions aimed at managing noise pollution.
Air Pollution and CO2
Figure 5 shows that while emissions of key pollutants like NOx and PM10 from vans and trucks have declined substantially from 1980-2011, CO2 emissions have remained essentially flat over that period. This is a concern given the growth in home deliveries and policy goals to drastically reduce transportation CO2 emissions.
The Whitebook goal is a near zero-emission urban delivery system by 2030. However, the current CO2 trajectory for vans and trucks, along with expected growth in home deliveries, makes this extremely ambitious. Regulatory measures for vans help, with mandated 14% and 28% CO2 reductions by 2017 and 2020 respectively. But more innovations are needed.
Potential mitigation strategies modeled could enable 60-80% CO2 emission reductions from 1990 levels by 2050, if measures are combined:
However, some options face limitations for broader adoption today, like cost, lack of infrastructure to support new vehicle technologies, lack of policy incentives, etc.
The Social Cost of Carbon (SCC) stands as a vital metric quantifying the economic impact associated with each metric ton of carbon dioxide emitted into the atmosphere. The data sourced from the Technical Support Document on the Social Cost of Carbon delineates SCC estimates spanning from 2015 to 2050, integrating various discount rates and statistical perspectives. This analysis portrays the economic implications of carbon emissions across diverse temporal and statistical scenarios.
The SCC estimates manifest notable fluctuations contingent upon distinct discount rates and statistical perspectives. At a 5% discount rate, the SCC initiates at $11 per metric ton of CO2 in 2015 and gradually ascends to $26 by 2050. Conversely, lower discount rates (3% and 2.5%) project higher SCC values, illustrating figures ranging from $36 to $69 per metric ton of CO2 in 2015, surging to $69 to $212 by 2050. The 'High Impact' scenario, representing the 95th percentile at a 3% discount rate, forecasts a higher SCC, starting at $105 in 2015 and culminating at $212 by 2050.
These estimations underscore the economic repercussions associated with carbon emissions, accentuating the substantial variation in SCC based on discount rates and statistical perspectives. Lower discount rates denote elevated SCC values, accentuating the augmented economic cost attributed to delayed mitigation actions.?
Congestion
Congestion caused by delivery vehicles incurs significant costs across various domains:
Firstly, the extra travel time resulting from frequent stops during deliveries significantly impacts overall traffic flow. Delivery vehicles' delays can be up to 3.5 times longer per mile compared to private cars, leading to substantial time spent on the road for all vehicles, especially in large cities where over 10 million delivery vehicle miles are common.
Moreover, these vehicles contribute substantially to environmental pollution. The start-stop nature of delivery operations reduces fuel efficiency and elevates emissions, releasing pollutants like particulate matter, nitrogen oxides, and carbon monoxide. Recent studies attribute a considerable portion of urban transportation emissions to medium and heavy freight vehicles, generating pollution externalities that cost metropolitan areas millions of dollars.
The safety implications are also profound. Delivery vehicles, due to factors such as driver fatigue and unsafe practices during loading and parking, experience crash rates 3-4 times greater than other vehicle types. Consequently, society bears significant costs in repair expenses, medical bills, and loss of life resulting from accidents involving delivery vehicles.
Furthermore, the extra fuel consumed by these vehicles exacerbates the situation. The constant acceleration, deceleration, and loading/unloading activities significantly reduce fuel efficiency, especially in urban settings. Parcel delivery vehicles, for instance, average only 10-12 miles per gallon in cities compared to over 30 on highways. With current elevated fuel prices, the additional fuel burned in congested urban driving becomes an externality not accounted for by delivery operators.
Introducing a formula to quantify the total cost of congestion in urban traffic, this calculation stems from the article titled "Method Research on Measuring the External Costs of Urban Traffic Congestion" published in the Journal of Transportation Systems Engineering and Information Technology in 2007. This formula serves as a structured approach to comprehensively assess the external expenses incurred due to congestion, offering a systematic method to evaluate the overall impact on various facets affected by urban traffic congestion.
Conclusion
This analysis provides a comprehensive overview of the multifaceted costs associated with last-mile logistics operations. Examining both direct and external expenses reveals the immense financial impact of the final delivery stage.??
Direct costs constitute a sizable proportion of total supply chain expenses, with labor, fuel, equipment, packaging, maintenance, and software collectively accounting for over 50% of overall costs. Variabilities in delivery times, routes, vehicle types, and recipient locations contribute to fluctuating operational costs.??
Moreover, externalities like accidents, pollution, noise, and congestion exacerbate cities’ infrastructure and environmental burdens. With road crashes costing nearly €38 billion yearly and noise pollution resulting in a €40 billion annual expense across the EU, curtailing these societal costs is imperative.
As online commerce proliferates globally, last-mile optimization is pivotal in bolstering customer experience while attaining profitability. The case study of open-source consolidation and route planning tools validates the effectiveness of pooling deliveries and charting efficient itineraries in reducing expenses.??
In summary, comprehensive data-driven analysis of last-mile costs coupled with targeted mitigation strategies can engender cleaner, safer urban mobility while upholding economic viability. Further research into innovative delivery models and continued infrastructural and regulatory enhancements can transform the last-mile segment.
References
In Alphabetical Order
Visser, J., Nemoto, T., & Browne, M. (2014b). Home Delivery and the Impacts on Urban Freight Transport: a review. Procedia - Social and Behavioral Sciences, 125, 15–27. https://doi.org/10.1016/j.sbspro.2014.01.1452