Want to cut costs and emissions in logistics? Route optimisation is the key.
Green logistics is reshaping how businesses manage deliveries, focusing on reducing emissions and improving efficiency. By 2050, logistics could account for 40% of global CO₂ emissions, making smarter operations critical. Here's how three approaches to route planning compare:
- AI-Driven Systems: Use real-time data and machine learning to cut emissions by 10–20% and improve delivery times by 15–30%. Ideal for large, complex operations but costly to implement.
- Manual Scheduling: Relies on human expertise but often leads to inefficiencies, higher emissions, and limited scalability. Best for small, predictable operations.
- GRS Fleet Telematics: A cost-effective middle ground offering real-time tracking, reduced emissions (15–30%), and scalability for just £7.99 per vehicle per month.
Quick Comparison
| Method | Emissions Reduction | Delivery Efficiency | Scalability | Cost |
|---|---|---|---|---|
| AI-Driven Systems | 10–20% | High (real-time updates) | Excellent (large-scale) | High initial cost |
| Manual Scheduling | Limited | Low | Poor | Low upfront cost |
| GRS Telematics | 15–30% | High (real-time tracking) | Excellent (affordable) | £7.99/month per vehicle |
To stay competitive and meet stricter UK regulations, businesses must adopt smarter logistics solutions. Whether you choose AI systems or cost-effective telematics, optimising routes is no longer optional - it’s essential for reducing emissions and cutting costs.
How To Reduce Your Logistics Costs With Route Optimization
1. AI-Driven Route Planning
AI-powered route planning is transforming the logistics world by improving efficiency and cutting emissions. By leveraging real-time data and sophisticated algorithms, these systems consider traffic, weather, vehicle performance, and delivery constraints to map out routes that minimise fuel use and maximise productivity.
Impact on Emissions
One of the standout benefits of AI route planning is its ability to reduce emissions. By cutting down on idling and avoiding the need for emergency shipments - often reliant on high-emission transport methods - AI systems help create a cleaner, greener delivery process. These tools constantly evaluate factors like traffic flow, road conditions, and vehicle efficiency to find the most fuel-saving paths.
The results speak for themselves. Studies show that optimising routes with AI can slash fuel consumption and emissions by 10–20%. Additionally, by improving how vehicles are loaded, these systems further enhance fuel efficiency and reduce the reliance on last-minute, expedited shipping.
Delivery Efficiency
AI systems don't just stop at cutting emissions - they also make deliveries faster and more efficient. By balancing travel distance, fuel use, delivery schedules, vehicle capacity, and driver availability, these tools optimise every aspect of the delivery process.
What sets AI apart is its ability to react in real time. If an accident, road closure, or sudden weather change occurs, the system predicts delays and reroutes vehicles instantly to avoid hold-ups. It also reassigns driver tasks to keep operations running smoothly.
Take FarEye's AI routing system as an example. It can allocate bulk orders in under 30 minutes, a task that used to take hours when done manually. Its "smart suggest" feature allows dispatchers to make quick, data-driven decisions, boosting productivity by as much as 25%.
Scalability
AI route planning is incredibly scalable, making it suitable for businesses of all sizes - from local operations to global logistics giants. These systems can handle sudden surges in demand, like those seen during holidays or emergencies, by redistributing resources efficiently. They’re especially effective in managing complex scenarios, such as multi-stop routes, tight delivery deadlines, and varying vehicle capacities.
Amazon provides a compelling example of AI's scalability. Its routing systems analyse customer orders and warehouse inventories to determine the best delivery strategies. This approach has enabled Amazon to deliver over 2 billion items with same-day or next-day shipping. In 2025, its automation efforts reportedly saved Prime members up to £77 billion on free delivery. The broader market for route optimisation software reflects this growing reliance on AI, with projections indicating it will grow from £6.3 billion in 2025 to £12.4 billion by 2030.
This scalability lays the groundwork for comparing AI systems with traditional manual scheduling methods in the next section.
2. Manual Route Scheduling
Manual route scheduling depends on human expertise and basic tools to map out delivery routes. While this method has been a mainstay for businesses over the years, its drawbacks are becoming harder to ignore - especially when considering its impact on fuel usage, emissions, and overall efficiency. Compared to modern automated systems, manual scheduling feels like a relic of the past.
Impact on Emissions
One of the biggest issues with manual route planning is its inefficiency, which often leads to poorly optimised routes. This results in higher fuel consumption and increased vehicle wear and tear. Drivers may find themselves retracing their steps or taking longer routes, adding unnecessary kilometres and driving up costs. Studies suggest that better route optimisation could cut fuel expenses and emissions by as much as 20%. For businesses sticking to manual methods, this represents a missed opportunity to significantly reduce their environmental footprint.
Delivery Efficiency
As delivery volumes rise, the cracks in manual planning grow more noticeable. Creating routes manually is not just time-intensive - it’s also prone to mistakes. Research indicates that manual planning can make routes take around 10% longer compared to automated systems. For a company managing 50 deliveries a day, this can mean an extra five hours of driving time daily. Such inefficiencies often result in vehicles overlapping routes, causing delays and operational headaches.
Jenna Aston from Paragon Routing highlights the broader consequences:
Manual route planning can be a significant drag on a company's performance and competitiveness. It can drain profits out of an otherwise healthy business. Worst of all, it can stand in the way of growth.
On top of this, manual planning struggles to adapt to unexpected issues like traffic jams or last-minute changes to delivery schedules.
Scalability
The biggest challenge with manual route scheduling is scalability. While it might work for small-scale operations, it quickly falls apart as businesses grow. Mapping out even 10 stops can take 30–45 minutes, and the accuracy largely depends on the planner’s expertise. As delivery demands increase, manual scheduling becomes a bottleneck, slowing operations and making growth difficult. Errors in routing waste fuel, lead to missed deliveries, and rack up redelivery costs, all while making it harder to estimate the financial impact of taking on more business.
Another drawback of manual methods is their inability to provide useful insights into delivery performance. Without data-driven analysis, businesses lose out on opportunities to improve efficiency. These limitations highlight the need for advanced systems like GRS Fleet Telematics, which can handle growing demands while keeping environmental concerns in check.
3. GRS Fleet Telematics
GRS Fleet Telematics offers a smart solution to the challenges posed by manual route planning, especially in terms of efficiency and environmental impact. With over 35 years of expertise through the GRS Group, this UK-based platform specialises in advanced van tracking systems. Its goal? To shrink carbon footprints while improving delivery performance. By combining cutting-edge route optimisation with reliable tracking technology, it provides a forward-thinking alternative to both manual and AI-driven systems.
Impact on Emissions
One of the standout features of GRS Fleet Telematics is its focus on reducing emissions. Using real-time GPS tracking and in-depth journey analytics, the system compares planned routes with actual ones, helping fleet managers pinpoint inefficiencies that lead to wasted fuel. It also monitors driving behaviours - such as acceleration, braking, and idling - alongside equipment usage. This data helps identify areas where fuel consumption and emissions can be cut, which is crucial as the logistics sector could contribute up to 40% of global CO₂ emissions by 2050.
Additionally, the platform tracks maintenance schedules and vehicle health metrics, ensuring fleet vehicles run at their best. Pilot programmes in the UK have shown that advanced route optimisation technology can reduce CO₂e emissions by 15–30% - a significant contribution to more sustainable operations.
Delivery Efficiency
Real-time GPS monitoring is another key feature that enhances delivery efficiency. Fleet managers can track vehicle locations and delivery progress, allowing them to respond quickly to unexpected issues like traffic jams or bad weather. The platform’s detailed journey analytics also highlight routing inefficiencies, enabling smoother and faster deliveries. On top of that, telematics data can be used to identify areas where drivers might benefit from additional training, creating a blend of technology and human improvement for better operational results.
Scalability
GRS Fleet Telematics is designed to grow with businesses, solving the scalability issues that make manual route planning less practical as operations expand. Pricing is straightforward and accessible, starting at just £7.99 per vehicle per month. This includes SIM card data, full platform access, and dedicated account management. The system also offers three hardware options to suit different needs and budgets:
- Essential (£35): A cost-effective single wired tracking solution.
- Enhanced (£79): Dual tracking capabilities for added functionality.
- Ultimate (£99): Includes immobilisation features for maximum security.
This flexible pricing and hardware structure allow businesses to start small and scale up as needed. The pay-per-recovery model, with no upfront recovery fees, further lowers financial barriers, making advanced fleet management a realistic option for growing companies. By combining scalability with environmental awareness, GRS Fleet Telematics sets a new standard for efficient and sustainable logistics.
Advantages and Disadvantages
When it comes to sustainable logistics, each method comes with its own set of strengths and weaknesses. Understanding these differences is key for businesses aiming to align their logistics with green goals.
Let’s start with manual route scheduling. This method is straightforward and works well for small-scale, predictable operations. Fleet managers who know their local areas can make decisions based on personal insights, customer relationships, and specific delivery needs. It requires little investment in technology and allows full control over routing. However, as businesses grow, this approach starts to show its limitations. Human error becomes more frequent, routes can become inefficient, and fuel consumption often increases. Since manual planning can’t adapt to real-time changes like traffic or weather, delays and unnecessary mileage are common.
On the other hand, AI-driven route planning offers a more advanced solution. These systems are designed to optimise routes by factoring in variables like traffic, weather, and vehicle capacity. Industry examples show this technology can lead to significant reductions in both emissions and fuel usage. Real-time adjustments can improve delivery times by as much as 15–30%. However, the high cost and technical complexity of AI systems can be a hurdle, particularly for smaller businesses. Additionally, implementing these systems often requires a solid data infrastructure, which not all companies have.
GRS Fleet Telematics stands out as a middle-ground option. It addresses the inefficiencies of manual scheduling while avoiding the steep costs and complexity of AI systems. This platform provides detailed analytics on driving patterns, route efficiency, and vehicle performance. With real-time GPS tracking, businesses can quickly respond to delivery challenges. Starting at an affordable £7.99 per month, it offers a cost-effective way for growing businesses to adopt smarter fleet management. Its data-driven insights also help companies improve fuel efficiency and cut emissions without needing a full AI setup.
Here’s a quick comparison of the three approaches:
| Method | Impact on Emissions | Delivery Efficiency | Scalability |
|---|---|---|---|
| AI-Driven Planning | High – optimises various factors for lower emissions | Very high – real-time adjustments improve delivery times by 15–30% | Excellent – handles large-scale, complex operations |
| Manual Scheduling | Poor – prone to inefficiencies and human error | Limited – lacks real-time adaptability | Poor – difficult to manage as operations grow |
| GRS Fleet Telematics | Good – tracks and improves driving behaviours | High – real-time tracking and analytics enhance routes | Excellent – scalable and affordable for businesses |
Choosing the right method depends on factors like company size, budget, and environmental goals. While AI systems are the most advanced, GRS Fleet Telematics provides a practical, cost-effective option with measurable benefits. Manual scheduling may still work for very small operations, but it becomes less viable as businesses grow and regulations around emissions become stricter.
With emissions concerns on the rise, this decision is becoming more urgent. Companies sticking to manual methods risk falling behind, while those adopting technology-driven solutions are better positioned to meet sustainability demands and thrive in a changing regulatory environment.
Conclusion
Different route optimisation methods cater to various business needs. For smaller, more predictable operations, manual scheduling might suffice, but it struggles to keep up as operations grow. On the other hand, AI-powered systems bring advanced capabilities to the table. For instance, UPS's ORION system processes over a billion data points daily, saving more than 10 million gallons of fuel annually and cutting carbon emissions by over 100,000 metric tons each year. However, such systems require significant investment and expertise. A more accessible option for growing businesses is GRS Fleet Telematics, which provides data-driven insights and real-time tracking for just £7.99 per month. This affordable solution bridges the gap between manual inefficiencies and the complexity of full AI systems, making it an attractive choice for UK companies aiming to improve fuel efficiency and reduce emissions.
The logistics industry is evolving rapidly, with trends like electrification, regulatory changes, and AI adoption driving the need for smarter, more sustainable solutions. Electrification, for example, is advancing quickly. The UK government’s plan to ban new petrol and diesel truck sales by 2035 is pushing fleet operators to transition to electric vehicles (EVs). Companies like DHL are already investing heavily, aiming to electrify a significant portion of their fleet by 2030. This shift necessitates route optimisation systems that can handle EV-specific challenges, such as limited battery range and the availability of charging points.
Regulations are also tightening as the UK works toward its net-zero emissions goal by 2050. Policies like the Transport Decarbonisation Plan and Streamlined Energy and Carbon Reporting (SECR) are introducing mandatory carbon reporting for many organisations. With transportation accounting for 27% of the UK’s total emissions in 2019, logistics companies are under increasing pressure to address their environmental impact.
AI is no longer a luxury but a necessity in logistics. It enables companies to cut fuel consumption by up to 25% while also improving safety, with 22% fewer accidents and 56% fewer unsafe driving incidents reported across fleets. These advancements make it clear that adopting advanced route optimisation is essential for fleets aiming to meet strict emissions targets.
Operational decisions today will shape how businesses adapt to future challenges. Logistics could account for as much as 40% of global CO₂ emissions by 2050. Delaying the adoption of technology-driven route optimisation could lead to falling behind competitors and failing to meet regulatory requirements. With around 80% of consumers now altering their shopping habits based on environmental concerns, the push for greener logistics has never been more urgent.
To succeed in this shifting landscape, businesses must choose optimisation methods that meet their current needs while preparing for future changes. Whether it’s starting with affordable telematics or investing in advanced AI systems, adopting scalable and efficient route optimisation solutions is no longer optional - it’s a necessity.
FAQs
How affordable and scalable is GRS Fleet Telematics for small and medium-sized businesses compared to AI-driven systems?
GRS Fleet Telematics: A Budget-Friendly Solution
GRS Fleet Telematics offers a wallet-friendly option tailored for small and medium-sized businesses, with prices starting at just £7.99 per vehicle per month. This makes it an appealing choice for businesses aiming to streamline their fleet operations without stretching their budgets.
On the other hand, AI-driven systems tend to come with a heftier price tag. Standard features typically cost between £25 and £45 per vehicle per month, and if you’re considering a custom-built AI system, development expenses can range from £9,000 to £29,000, depending on complexity. While these systems offer advanced tools like automation and predictive analytics, they’re often better suited for larger organisations with more intricate operational requirements.
For smaller businesses that value affordability and flexibility, GRS Fleet Telematics delivers a cost-effective solution. It provides essential features like advanced tracking and security, ensuring you don’t have to compromise on quality while keeping expenses under control.
How does AI-driven route planning help reduce emissions and enhance delivery efficiency?
AI-powered route planning is transforming delivery logistics by cutting down emissions and boosting efficiency. By calculating the most fuel-efficient routes, it helps reduce unnecessary mileage, limits idle time, and adapts in real time to factors like traffic or weather. The result? Smarter fuel use and lower carbon emissions.
This streamlined approach not only helps businesses save on fuel expenses but also supports their environmental goals. Plus, it enhances customer satisfaction with quicker, more dependable deliveries.
Why do some businesses still use manual route planning despite the advantages of automated systems?
For some businesses, sticking with manual route planning remains appealing due to the control and flexibility it offers, especially in situations that are complex or prone to sudden changes. Smaller companies or those hesitant to commit to new technology often see manual planning as a more cost-effective option at first, as it eliminates the need to invest in specialised software.
Another advantage of manual scheduling is the ability to provide a personalised touch to customer service. It allows businesses to make real-time adjustments based on feedback from drivers or specific customer needs. While automated systems are efficient, many businesses still appreciate the adaptability and human element that manual planning brings to the table.
