As the demand for last mile deliveries has exploded in recent years, delivery costs have risen sharply as well. With labor, fuel, vehicle expenses and more, last mile delivery now represents over 50% of the total cost of shipping for many companies. As a result, businesses are looking for ways to optimize their routes and lower costs without impacting customer service. 

Route optimization software has emerged as an effective solution to reduce last mile delivery costs through more efficient routing and scheduling. In this comprehensive guide, we’ll explore how route optimization can lower costs, key features to look for in software, implementation best practices, and real-world examples of cost savings. 

The Rising Costs of Last Mile Delivery

The last mile of delivery – the final leg from a transportation hub or warehouse to the customer’s door – is widely considered the most expensive and inefficient part of logistics. As buyers expect faster and more flexible delivery options, last mile costs have climbed even higher. 

Some key stats on rising last mile delivery costs:

– Last mile accounts for 41% of total shipping costs on average

– Last mile costs are estimated at $10-$20 per parcel on average

– Costs per stop can range from $2 for dense urban areas to $10 for rural areas

– Fuel, labor, and vehicle expenses account for over 75% of last mile delivery costs

With the growth in ecommerce and consumer expectations for fast, low-cost shipping, volumes are rising. But last mile networks are often inefficient – routes aren’t optimized, trucks drive miles with empty capacity, and schedules are assembled manually.

These inefficiencies add costs in nearly every area:

– More mileage and fuel expenses: Vehicles often crisscross areas unnecessarily or have deadhead miles returning to the warehouse. Increased route efficiency can reduce mileage substantially.

– More vehicles and drivers needed: Without route optimization, delivering the same volume requires more drivers and trucks driving overlapping routes. Effective planning fills routes to capacity.

– Higher labor costs: Inefficient routes take more driver time, resulting in inflated labor costs and lower driver productivity. Streamlined routes get more done with fewer hours.

– Congestion and reattempts: Poor route plans lead to more miles in congestion and missed first attempt deliveries, requiring expensive reattempts. Optimization provides more accurate delivery windows.

Facing shrinking margins as customer demands grow, companies are turning to technology for relief. Route optimization software is an attractive solution to reduce the rising costs of last mile delivery.

How Route Optimization Software Can Reduce Costs 

Route optimization leverages algorithms and routing engines to design the most efficient routes possible given constraints like drivers, vehicles, road networks, traffic patterns, service times, and more. By optimizing every route to minimize mileage, time, and resources, businesses can achieve significant reductions in last mile costs.

Here are some of the ways route optimization drives down costs:

More Efficient Route Planning

At its core, route optimization software creates routes that use less mileage and fewer resources by analyzing factors like:

– Real-time and predicted traffic when planning routes

– Driver availability, shifts, skills and locations

– Service times at each stop 

– Vehicle capacity and limitations

– Road speeds based on topology, congestion patterns and more

– Grouping stops into runs that minimize deadhead time and mileage

By accounting for all constraints, route optimization often designs plans that use 40-50% fewer miles than routing assembled manually by dispatchers. And it does this while maintaining customer service levels.

Reduced Mileage and Fuel Costs

With route optimization, drivers take the shortest paths possible between stops. By eliminating excess driving distance within routes, businesses can significantly cut fuel consumed.

Some metrics from route optimization users:

– 10-30% reduction in miles driven per day

– 20-35% less fuel consumed per driver

– 15% lower carbon emissions

Since fuel is one of the largest variable costs in last mile delivery, reducing mileage directly translates into cost savings. Route optimization enables the same volume of deliveries with fewer miles and lower fuel spend.

Fewer Vehicles and Drivers Needed 

Optimized routes also allow companies to use fewer drivers and trucks to complete the same number of deliveries. Instead of disparate drivers crisscrossing a zone, route optimization creates consolidated routes that maximize every truck’s capacity and keep drivers in tight geographic clusters.

This allows managers to:

– Complete all deliveries with 10-30% fewer drivers per day

– Eliminate or reassign excess trucks/vans as volumes shrink

– Adjust staffing efficiently during seasonal peaks and valleys

With optimized routes, each driver and vehicle can handle more stops per shift. That means paying fewer driver hours and making better use of fixed vehicle assets – directly reducing costs.

Increased Delivery Capacity 

Along with using resources more efficiently, optimized routing unlocks capacity to handle more deliveries without adding vehicles or staff.

Route optimization allows companies to:

– Increase stops per driver by 25-50%

– Add 20-30% more deliveries per day with the same fleet and labor

– Absorb spikes in volume during peak seasons with existing resources

This added capacity is extremely valuable in competitive, high-growth segments like ecommerce where volumes are surging. Unlocking more delivery capacity helps businesses capture more market share without inflating costs.

Reduced Labor Costs

In addition to needing fewer drivers and trucks, route optimization also reduces the time spent completing routes. With less deadhead driving between stops, drivers can finish routes faster. And when routes align closely with driver shifts, it avoids overtime.

This translates into:

– Each driver spends 15-25% less time per route

– Drivers complete 5-10 more stops per 8-hour shift

– Less need for overtime during peaks

These labor efficiencies mean lower cost per delivery. Fitting more stops into each paid labor hour increases productivity and control over the largest single cost for last mile delivery – driver wages.

Key Features of Route Optimization Software

To maximize cost savings, route optimization software should incorporate certain key capabilities:

Powerful algorithms 

At the core of any route optimization engine is its algorithms – the set of mathematical processes it uses to calculate efficient routes. The best tools leverage complex algorithms like machine learning and simulated annealing to quickly identify the lowest cost route options.

Algorithms should account for all delivery constraints and traffic conditions and get continually updated. Look for algorithms with a proven track record of generating high-quality routes.

Real-time traffic updates

Traffic jams and congestion can quickly invalidate routes. The software should integrate with live traffic databases and automatically update routes as conditions change. This allows drivers to avoid delays and complete routes faster.

Flexible route planning

Not all delivery routes have the same constraints. A good routing engine offers customizable planning to handle:

– Single driver routes vs relay routes with handoffs 

– Delivery vs pickup routes

– Dense urban environments vs rural spread out stops

– Vehicle size, weight, and temperature requirements

– Driver skills and availability  

– Road restrictions like hazmat, weight limits

With flexible planning, companies can optimize different route types for lower costs.

GPS tracking and telematics 

Most route software integrates with truck GPS devices to track location and transmit progress back to the planning engine. This allows real-time route updates as stops are completed.

Route data can also connect to telematics for engine diagnostics, temperature monitoring, driver behavior, and maintenance alerts. This improves field operations.

Route optimization reporting 

Robust reporting helps managers measure optimization results and fine-tune over time. Key reports to look for:

– Route performance – planned vs actual route time, mileage 

– Driver efficiency – stops, mileage, hours per shift 

– Delivery statistics – on-time rate, exceptions

– Maps and route visualizations

– Cost savings projections and actuals

Implementing Route Optimization Software

Transitioning to route optimization involves careful planning and execution. Follow these best practices to ensure a smooth and successful implementation:

Assessing current routes and costs

Before selecting software, take time to analyze current routing processes and costs:

– Audit a sample set of current planned routes versus actual driver routes 

– Identify unnecessary miles driven and inefficient clusters of stops

– Calculate cost per stop/delivery based on mileage, time and resources used

– Map out delivery density patterns and current fleet distribution

This baseline helps determine optimization potential and serves as a starting point to measure results after implementation.

Choosing the right software

Look for route optimization software that best matches business requirements based on:

– Delivery workflow – pickup vs delivery, route types, driver handoffs 

– Route volume – number of routes per day/week/month

– Fleet profile – vehicle types, capacities, limitations

– Driver workforce – shifts, labor rules, skills and certifications

– Cost structure – focus on reducing mileage, labor time, etc

– IT landscape – needed integrations, data sources, and infrastructure

Seeking demos and free trials can determine which solution provides the strongest results.

Integrating with existing systems

Route software should integrate with critical enterprise systems for real-time data exchange:

– Warehouse Management Systems – Pull delivery orders, inventory status, packing data

– Fleet Telematics – Transmit routes, track location and status

– Driver Apps – Push routes to drivers, record proof of delivery

– CRM/ERP – Sync completed deliveries, exceptions, customer data

APIs and connectors should make integrations straightforward. Validating integrations works during an initial pilot before scaling to full deployment.

Driver training and adoption

The optimization engine creates routes, but drivers ultimately execute them on the road. Thorough training ensures drivers understand how to:

– Access assigned routes on their device

– Follow dynamic routing guidance

– Report any delays or exceptions

– Maximize delivery efficiency each day

Drivers should provide ongoing feedback so routes can be refined over time. Management should reward drivers for adopting optimization practices.

Start with a pilot before expanding 

The best practice is starting with a small pilot – selecting a subset of vehicles or geographic zones to optimize first. Gradually expand the rollout based on learnings. This allows time to gather data, address any issues, and demonstrate benefits before company-wide deployment.

Measuring Cost Savings and ROI

Once route optimization is live, companies monitor a set of KPIs to quantify benefits and ROI:

Route Efficiency

– Reduced miles per route 

– Stops per route increase

– Lower route time

Asset Utilization

– Increased stops per driver per shift

– Higher percentage vehicle fill

– Reduced overtime

Delivery Costs 

– Fuel cost per stop/per route

– Labor cost per stop/per route

– Maintenance costs per mile

Service Metrics

– On-time delivery rate

– Exceptions and missed deliveries

– Customer satisfaction scores

Tracking metrics before and after optimization highlights achievable cost reductions. Companies typically see a full ROI within 6-12 months after implementation.

Case Study: Delivery Company Sees 20% Cost Reduction  

Let’s look at a real-world example of savings from route optimization:

ABC Delivery is a regional carrier serving 150,000 residential and commercial customers across 20 service zones. They operate a fleet of 50 trucks making 1,500 deliveries per day. 

The Challenge: ABC struggled with rising fuel and labor costs while trying to keep up with growing volumes. Dispatchers spent hours manually assigning routes, but inefficient routing meant drivers crisscrossed zones and racked up excess mileage. ABC needed to reduce costs substantially without harming service quality.

The Solution: ABC adopted Routerunner, a dynamic route optimization solution, to automate route planning. By optimizing routes each day based on real-time traffic, volumes, driver shifts and other variables, Routerunner increased route density.

The Results:

– Reduced 100,000 miles per month driven, a 22% improvement

– Saved $18,000 per month in fuel costs

– Increased stops per driver by 30%

– Cut overtime expenses 23%

– Added capacity for 25% volume growth without adding staff

– Achieved 20% lower cost per delivery

Route optimization delivered measurable benefits from the start. The company achieved full ROI in less than 10 months while improving customer service.

Best Practices for Ongoing Optimization

Route optimization should become an always-on business capability. Follow these best practices for continuous cost improvement after initial implementation:

– Provide sufficient volume history – The routing engine improves as it collects more data over time. Provide at least 6 months of historical routes and volumes.

– Set optimization strategy – Determine focus areas like reducing driver overtime, increasing delivery density, or minimizing mileage. Adjust parameters to align software with strategy.

– Leverage interactive planning – Let the system create an initial optimized plan, then dispatchers can manually adjust routes before finalizing if needed. Combining human insight with algorithms gets the best results.

– Refine over time – Manager can tweak route planning rules, constraints, exceptions and access as needed. Refining the configuration and integrating new data sources improves optimization daily.

– Monitor KPIs – Track route optimization metrics on driver efficiency, cost per stop, customer service and more. Rapidly identify areas needing improvement.

– Get driver feedback – Drivers know where routes don’t match the real world. Get their input on difficult pickup locations, inaccurate service times, and other refinements to improve routes over time.

– Retrain periodically – Refresh training for dispatchers and drivers on route practices and software updates. Change management boosts adoption.

With continuous attention, route optimization keeps driving lower costs as business conditions evolve.

The Future of Delivery Route Optimization 

Route optimization technology will continue advancing as adoption accelerates:

– EV routing – Electric fleet charging constraints will be integrated into planning. Machine learning will predict range and charging needs more accurately.

– Predictive modeling – Platforms will forecast future demands, traffic disruptions, and other variables to optimize upcoming routes in advance.

– Dynamic re-routing – Routes will automatically adjust in real-time based on current traffic, new orders, and changing conditions versus just fixed daily plans.

– Integrated workforce tools – Scheduling, timekeeping, job management and other HR tools will integrate natively with routing for end-to-end operations.

– Autonomous delivery – As robots and drones scale up for last mile delivery, route optimization will incorporate autonomous vehicle constraints for curbside handoffs, charging, and more.

Route optimization is on track to become an essential tool for efficient, profitable last mile delivery as competition and demands intensify.

Conclusion

With the rapid growth in last mile delivery, rising costs threaten margins for companies without optimization strategies. Route optimization technology offers a proven way to reduce mileage, labor, fuel and maintenance costs without sacrificing service. 

Core benefits like increased route density, fewer miles driven, and more deliveries per driver add up to significant savings. Route optimization typically provides ROI within 6-12 months of adoption. And the scalability unleashes capacity for business growth.

As same-day and next-day delivery becomes standard, route optimization will only increase in importance. By leveraging the latest optimization engines, delivery businesses can contain costs while meeting customer expectations now and in the future.