Understanding the hurdles: Challenges of traditional route planning

 Drive business efficiency, boost sustainability and optimize costs with AI logistics solutions

Before discussing how AI reshapes everything, it's best to understand why it's vital. The traditional approach best covers this through the hurdles of the traditional approach. 

While numerous limitations increase costs and reduce efficiency, traditional planning has always been filled with gaps and unpredictability. Here are the key challenges that gave way to AI logistics solutions:

• Outdated data usage: Data is quite dynamic and needs constant updates. Traditional route planning relied on static, obsolete data, often resulting in inefficient routes and higher operational costs.
• Inability to handle disruptions: Your business can handle disruptions only with some foresight. Traffic jams, accidents, and weather changes were regular struggles in traditional route planning. This eventually led to derailed delivery schedules, with no real-time tools to adjust routes.
• Regulatory complexities: Import/export requirements are quite administrative and location-specific. Pre-requisites often include customs clearance, tariffs, and compliance laws across borders. Traditional route planning is a reactive approach that delays and burdens international shipments.
• Rigid routing systems: Traditional planning lacks the flexibility to adjust routes in real time or respond to sudden changes in demand. It also hinders scalability and agility for logistics managers coordinating with larger fleets. This is especially inefficient when operating in multiple lanes with varied complexity.
• Higher operational costs: Traditional route planning often leads to longer routes, more time spent on roads, and in-efficient routes. Increased fuel, labor, and maintenance expenses create a domino effect. Unplanned varying costs such as tolls and congestion fees also impact the entire costing exercise.

The threat of a sluggish supply chain is why businesses demand machine learning in supply chains. Route optimization software is now a 6.1 billion dollar market with AI experts like Pando at the forefront.

Spotlight on the solution: How AI drives logistics optimization

Traditional logistics systems often create a rigid and inefficient supply chain. With such dire consequences on the line, any new solution feels inherently risky. A clear understanding helps bridge trust and confidence in technologies like AI. 

Which begs the question: How do AI logistics solutions actually work? 

AI, as the name suggests, is all about bringing intelligence into your supply chain. While the result may be AI efficiency optimization or cost-saving logistics strategies, the core drives insights and improvement. So before we get to the benefits of the applications, here's a break down on how AI optimizes delivery routes:

• • Gather data: AI collects real-time information such as traffic, weather, vehicle locations, and historical delivery patterns.
  • Analyze and predict: AI studies this data to spot trends, anticipate problems, and see how conditions affect routes. 
  • Create best routes: AI designs routes considering distance, speed, fuel use, vehicle capacity, delivery times, driver availability, and any sudden changes. 
  • Guide and monitor: Drivers get the optimized routes, and AI monitors the situation, tracking progress and handling surprises. 
  • Learn and improve: AI learns from each delivery, getting better at making routes even more efficient over time. 

If you're wondering what the end of this sequence leads to, here are the results:

• • Drives process efficiency: These solutions optimize how you create and manage supply routes 
  • Optimizes logistics cost: Your business plans vehicles only when necessary and follows the ideal routes. This reduces logistics costs such as fuel consumption and empty miles 
  • Saves time and effort: AI solution eliminates the manual chaos and effort of delivery planning. It even saves you time spent in fire-fighting disruptions 

Here are a few more quick use cases to highlight how AI-driven logistics optimization works: 

• • Load and delivery prioritization: AI algorithms can assess delivery’s urgency, load requirements, and size. With these details added to the AI model, developing prioritized loading and delivery becomes seamless. For example, high-priority or time-sensitive deliveries are automatically scheduled for earlier stops, and routes are optimized around them. 
  • Fleet-specific optimization: Another key application for AI is space optimization. By analyzing each vehicle’s load capacity, AI generates optimal load plans. Through intuitive use of space, AI models also maximize resource use and reduce operational costs. For example, huge cartons that need to be delivered at the first stop will be assigned the right spot at the back of the truck. 

It sounds almost too powerful to believe, right? Supply chain AI experts like Pando have solutions, such as transportation management systems (TMS), that make this an everyday accessible super solution. 

Next up, we dive deeper into the benefits of AI-driven logistics optimization.

Understanding the Impact: Benefits of AI in Logistics Optimization 

We've now covered an AI solution's approach. While this does explain how AI reshapes traditional planning, effectively adopting it requires an in-depth understanding of its benefits. 

Diving a little deeper into that, here are the benefits of AI in three crucial logistics optimization functions. 

AI in route optimization

AI-powered route optimization involves avoiding obstacles, planning routes, and reviewing customer and supply availabilities. Here are the benefits AI route optimization can offer your business:

• Reduced fuel consumption: Optimized routes minimize mileage and avoid traffic congestion, leading to significant fuel savings. Less fuel burned translates to lower operational costs and a reduced carbon footprint. 
• Shorter delivery times: Efficient routes and real-time adjustments ensure faster deliveries, enhancing customer satisfaction. Timely deliveries also open up new business opportunities and improve overall efficiency.
• Improved driver safety: Machine learning in supply chains can identify and avoid hazardous routes or weather conditions, protecting drivers and cargo. Reduced accidents and improved safety lead to lower insurance costs and increased driver well-being.

With AI in transportation execution, businesses can automate multi-model triggers. These AI applications also synchronize the best route with the ideal freight mode. Supply chain experts like Pando have already driven change for numerous MNCs worldwide. Castrol, the British Oil Company, says, "Pando TMS helped plan routes, reduce fuel consumption, and improve efficiency."

AI in freight procurement

Delivery routes are often about real-time operational improvements. AI also drives improvements in strategic functions such as freight procurement. 

AI logistics solutions in this function involve boosting your contract negotiating power, predicting freight rates, and optimizing RFQ lanes in real-time. Here are the key benefits of AI in freight procurement:

• Optimized vendor lane allocation: AI logistics solutions such as intelligent bid analysis ensure the most suitable vendors are selected based on cost, reliability, and performance history. Experts like Pando also drive efficient resource allocation and maximize the value obtained from each vendor.
• Cost savings: AI-powered procurement tools, such as Pando's freight procurement, also use predictive analytics to forecast freight rates. These cost-saving logistics strategies give your business a better footing during contract negotiations. AI in logistics optimization also expedites the overall RFQ approval process.
• Improved efficiency: Streamlining the procurement process with AI reduces manual effort and accelerates decision-making. This frees up valuable time for logistics professionals to focus on strategic initiatives and value-added activities.

AI in freight audit and payment

Logistics doesn't stop at delivery. Carrier payments quickly follow every shipment. Here, AI in freight audit involves invoice verification and payment release. Here's how your logistics optimization benefits from AI in freight audit:

• Reduced errors: AI in pre-freight auditing validates invoice details and resends them for correction. Pando's automated freight auditing ensures no errors reach the payment stage and boosts efficiencies.
• Faster payment: Supply chain AI experts like Pando help automate payment approval, reducing manual processing time. AI-driven payment solutions deliver faster payment cycles and strengthened vendor relationships
• No overcharging: With a contract database as a reference, AI cross-checks invoices against agreed rates and clauses. This prevents overbilling and flags discrepancies before payments are processed. Along with cost control, AI solutions also make carrier and freight mode selection seamless.

AI's benefits are wide-ranging. It's safe to say AI-driven logistics optimization is a powerful way to begin reshaping your business.

AI in action: Success stories in the U.S

The potential benefits of AI logistics solutions are quite clear. However, the actual proof comes from knowing where these cost-saving logistics strategies can succeed. 

Here's an example of how a parts manufacturer used cutting-edge AI solutions to optimize visibility and freight spend:

Accuride: Cut freight spend by millions 

Amid multiple supply chain disruptions, including the Suez Canal crisis, US auto parts manufacturer Accuride identified a key challenge: transportation visibility and exorbitant freight costs. Their solution? Embracing Pando's AI-powered solution. 

With Pando's phased implementation, Accuride instantly introduced real-time shipment tracking into their supply chain operations. Along with Pando’s platform to centralize logistics data, they unlocked freight spend analytics and invoice auditing. Accuride also began paying only relevant accessorial charges and selecting the right carriers. 

Accuride soon saw tangible results. They reduced ocean freight costs by 6.5%, eliminated inefficiencies, and produced 1.5 million dollars in annual savings. 

The organization's logistics processes are now a clear competitive advantage.

Transforming and optimizing logistics operations with Pando

AI is redefining logistics, from streamlining movement to optimizing freight costs. The in-depth concepts we've covered in this guide highlight AI's transformative potential. 

Considering all these insights, incorporating AI for logistics optimization is the need of the hour for your business. All that's left is to partner with the right supply chain AI expert and advance to the forefront of AI transportation. 

That's where you'll find Pando. 

With its advanced TMS, Pando optimizes delivery routes, streamlines operations, and ensures seamless supply chain execution. From smart route planning to strategic freight procurement, Pando drives cost efficiency and enhances operational agility. 

Pando also seamlessly leverages predictive analytics to cut costs and align logistics with broader business goals. 

If you're thinking of upgrading to AI logistics solutions, it's time to try Pando. 

Book your demo today!