According to a McKinsey survey, freight and warehousing are responsible for 7% of global greenhouse gas emissions. Scope 3 emissions refer to those generated indirectly through supply chain activities rather than a company’s own operations.
As the race to achieve net-zero intensifies, enterprises are finding ways to decarbonize logistics.
One solution that many enterprises are adopting is intelligent routing.
Before diving into how intelligent routing works, let’s examine how existing route planning contributes to high carbon emissions.
Why Is Existing Route Planning Ineffective?
Typically, enterprises look for the shortest, fastest routes. These routes are determined by historical data and driver knowledge. However, the problem with this approach is that enterprises don’t consider the following factors:
Traffic congestion: While a map might show a clear route, it cannot anticipate sudden traffic snarls. This leads to vehicles spending more time idling and emitting carbon into the air.
Unoptimized route planning: Sometimes, unoptimized routes can result in longer distances, more detours, and higher fuel consumption.
Other variable conditions: Traditional route planning does not account for dynamic factors such as road conditions, elevation changes, and weather. This leads to vehicles consuming more fuel and increasing their carbon footprint.
With intelligent routing, enterprises can reduce emissions and achieve their sustainability goals.
What Is Route Optimization Software and How Can It Reduce Carbon Emissions?
Route optimization software is a tool that logistics enterprises use to plan routes based on factors such as road conditions, weather, traffic, vehicle capacity, and delivery windows. The objective is to reduce waiting time, improve delivery performance, and decrease carbon emissions.
Let’s look at two examples of how intelligent route optimization can enhance sustainability outcomes.
A study was conducted on two trucks (a waste collector and a tree maintenance truck) in Blacktown City, Australia, to evaluate the efficiency of route optimization. A route optimization model was run on both of them, taking into consideration the complexities of route planning.
The result: the study found that by using the optimized route, the tree maintenance truck reduced fuel consumption and greenhouse gas emissions by 62% per month. The waste collector truck, on the other hand, reduced monthly greenhouse gas emissions by 10% and fuel consumption by 11%.
The impact of route optimization was also seen when UPS used a routing software called On-Road Integrated Optimization and Navigation, or ORION, to optimize routes and decrease fuel consumption and carbon emissions. ORION helped UPS avoid driving over 100 million miles, resulting in a 100,000-metric-ton decrease in annual carbon emissions.
Here’s how Intelligent Routing Delivers Measurable Sustainability Impact:
Optimize Routes: The route optimization software uses complex algorithms and variable factors to determine the best route for a trip. For example, it considers all pick-up and drop-off points, traffic patterns, and other factors such as vehicle capacity and delivery schedule. Based on these conditions, the software calculates the distance and travel time and recommends the best route. The software then sends the routes to the assigned drivers so they can drop off products on time.
Schedule Deliveries: With route optimization software, enterprises can schedule drop-offs and deliveries based on factors such as weather conditions and traffic jams. It can also recommend solutions such as dropping off goods during off-peak hours or combining multiple deliveries. This will reduce the waiting period, the need for making repeated trips, and decrease fuel consumption and emissions.
Enhance Resource Utilization: Route optimization software enables enterprises to maximize fleet utilization and reduce the number of trips. This improves resource utilization and reduces environmental impact without compromising service levels.
Avoid Traffic Jams: Emissions rise during traffic jams when vehicles are idle. With route optimization software, enterprises can access real-time route data and direct vehicles to reroute to avoid traffic jams.
The Role of AI and IoT in Intelligent Routing
For intelligent route planning, enterprises require a combination of AI in logistics and IoT technologies. IoT gathers real-time data on vehicle location, temperature fluctuations, traffic, and road conditions through RFID tags, cargo monitors, and telematics. AI, on the other hand, leverages this real-time data to identify patterns, predict bottlenecks, and recommend solutions such as rerouting. Together, these technologies help enterprises reduce idle time, fuel consumption, and emissions.
How CSCS AI+IoT Solutions Help Enterprises Achieve Sustainability
At CSCS, we understand the challenges enterprises face in optimizing routes and achieving sustainability goals. The problem lies in fragmented legacy systems that operate in silos. To reduce carbon emissions, increase revenue, and save on freight and labor costs, enterprises need a unified system.
That’s where our AI-powered platform helps.
It helps enterprises with:
Seamless integration of legacy systems: We provide AI-powered connectors such as APIs, EDI, and JSON to unify fragmented systems and ensure seamless data exchange across TMS, WMS, ERP, and IoT systems. We help eliminate manual intervention and automate workflows from purchase order (PO) to delivery.
Improved supply chain visibility: We merge operational and IoT data to provide a holistic, real-time view of the supply chain—from inventory management to shipping and asset tracking. We also offer IoT-based monitoring to prevent damage to goods (e.g., due to temperature fluctuations) and proactively send alerts that resolve problems.
Increased optimization: Our platform helps enterprises optimize processes such as route selection, warehouse automation, and demand forecasting using AI reducing costs and improving supply chain efficiency.
By improving processes and eliminating data silos, we help enterprises reduce their carbon footprint and achieve sustainability.
How To Get Started?
Planning to reach your sustainability goals within the next three months? Here’s a roadmap to get started.
0-30 days: Identify a specific process, such as route optimization, or a use case such as high-friction lanes that need immediate attention. Assess existing workflows, integration readiness, and resource capabilities before launching the AI pilot. Conduct a carbon emissions audit to evaluate the impact of the AI-powered solution.
31-60 days: Go live with the AI workflows and continue tracking the KPIs. Iterate the workflows to achieve sustainability goals.
61-90 days: Scale to other operations and processes that contribute to carbon emissions, ensuring the entire organization becomes more sustainable.
For more information about our platform, contact us.
Frequently Asked Questions (FAQ)
Q. Why Is Traditional Route Planning Ineffective?
Traditional route planning relies on static, historical data and human insights. It often fails to factor in variables like traffic jams and road conditions, leading to more idle time and unnecessary fuel emissions.
Q. How Do AI and IoT Improve Route Optimization?
While IoT gathers real-time data from RFID tags, cargo monitors, and telematics, AI uses the data to identify patterns and predict bottlenecks. It alerts teams and recommends solutions, such as rerouting, to reduce idle time and emissions.
Q. How Can Enterprises Implement AI-Based Route Optimization?
Avoid ad hoc implementation. Take a step-by-step approach of assessing existing workflows, prioritizing a use case, tracking KPIs, iterating the process to make improvements, and scaling across other functions.