How Predictive Analytics is Accelerating Last-Mile Delivery?

If you’ve ever received a notification from Amazon that your product is out for delivery, you know what last-mile delivery looks like. 

It is the last stage in the delivery of a product to a client or a customer.

As a result of growing supply chains, the global last-mile delivery industry is now worth $175.3 billion, with the US last-mile market already worth $29.9 billion

But that’s not all. In 2023, last-mile delivery costs comprised 53% of global shipping costs, up from 41% in 2019. 

Thus, last-mile delivery operations are facing increasing challenges. These include rising costs, increased run times and customer satisfaction. 

As a result, supply chain management enterprises are increasingly looking to leverage predictive analytics to solve last mile delivery challenges in supply chains. 

In this blog, we’ll take a look at how predictive analytics are transforming last-mile delivery operations. We’ll also see why it is becoming indispensable to the last-mile delivery industry. 

The Latest Trends of Last-Mile Delivery

Before discussing the revolutionary potential of predictive analytics in accelerating last-mile delivery, let’s see some of the latest developments in last-mile operations: 

Autonomous Vehicles

Along with driving us to our destinations, self-driving vehicles also play an important role in delivering products to end customers. 

Especially since the pandemic, self-driving vehicles have been recognized as the future of last-mile delivery. 

This is evident in the investments made by American companies like DoorDash and Uber and Chinese companies like JD.com.

Long story short, autonomous vehicles are slowly but surely being deployed more frequently for last-mile delivery operations. And this phenomenon is global! 

Naturally, predictive analytics play a pivotal role in powering and maintaining these vehicles.

Same-Day and Next-Day Delivery

If you’ve ever needed an emergency birthday gift or a new phone because your old one has broken down, you know the importance of same-day or next-day delivery. 

In a world where more and more essential goods, such as food and medicine, are being purchased online, same-day and next-day delivery have become as common as regular deliveries. 

But expedited deliveries also come with a host of challenges. 

For instance, if you’re a company that offers same-day delivery, you’ll need to know in advance where to locate your warehouses and delivery fleets and how to organize your delivery schedules. 

Thus, next-day or same-day deliveries would be impossible without predictive analytics in logistics!

Delivery Drones

Another advancement in last-mile delivery is the use of drones. 

It goes without saying that drones are much faster than autonomous vehicles. After all, they just zoom over obstacles, traffic or congested streets. 

Plus, like autonomous vehicles, they require minimal human oversight. 

As of 2024, several companies have already received permission from the FAA to make small-distance drone deliveries to customers. 

Use of Advanced Telematics 

Telematics combines the power of advanced communication and GPS technology. It allows fleet managers to locate and interact with drivers and vehicles in real-time. 

Over the last ten years, telematics has advanced in technology and deployment. It can help fleet managers:

• Log delivery times, 

• Observe and compare delivery schedules,

• Provide on-the-go assistance to drivers and

• Monitor asset health. 

Today, advanced telematics has become an integral part of logistics operations and last mile delivery solutions. 

IoT Integration

The Internet of Things is the virtual ecosystem comprising different electronic devices connected by a common network. 

IoT devices are critical to last-mile delivery as they:

• Measure last-mile driving time, 

• Log route conditions and 

• Help provide real-time assistance to the drivers. 

An Electronic Logging Device (ELD) is a prime example of IoT integration. It records vital data, including driving patterns, fuel consumption, weather events and vehicle health. 

It thus creates a treasure trove of information that companies can use to optimize last-mile delivery logistics. 

Smart Glasses for Delivery Optimization

Smart glasses are another example of how last-mile delivery operations are being transformed through predictive analytics. 

Recently, Amazon invested billions into making smart glasses a reality. Their function? To utilize predictive analytics in logistics and give drivers street-by-street driving instructions.

The aim is to ensure route optimization, reduce driver error and increase efficiency. The smart glasses, internally referred to as Amelia, bring together the power of advanced telematics and IoT integration. 

As we can see, logistics companies are sparing no money when it comes to optimizing their last-mile delivery infrastructure. 

And predictive analytics is at the heart of these investments! 

The Role of Predictive Analytics in Transforming Last-Mile Delivery

And now, we come to the meat of the matter: the role of predictive analytics in the multi-billion-dollar last-mile delivery industry. 

Predictive analytics refers to the process of understanding the past to predict the future through computational tools like machine learning algorithms. 

Let’s understand this simply. 

Say your last 10 deliveries each took 20 minutes to complete. The goal of predictive analytics is to detect a pattern of actions that can be removed from the process to reduce this time to 18 minutes. 

With another iteration, we can knock off another couple of minutes. We can repeat this process until 20 minutes are reduced to 12-15 minutes, saving you at least 50 minutes of last-mile delivery time! 

Thus, predictive analytics helps you solve last mile delivery problems by combing through thousands of data points to isolate the signal from the noise. The objective is to make your operations as smooth and profitable as possible. 

Here’s how predictive analytics can be used to tackle different aspects of last-mile delivery: 

Predictive Analytics Optimizes Last-Mile Delivery Routes

From critical minerals to life-saving medicines, faster delivery times are becoming increasingly vital to people and companies. 

Route optimization is one of the easiest ways to satisfy this demand. 

It is also one of the most common applications of predictive analytics. As with weather prediction, predictive analytics can yield very strong results when applied to repeated events. 

Using predictive analytics, an ML algorithm can determine which route is the fastest or the shortest for a given set of destinations. It ensures:  

• Shorter delivery times,

• Timely delivery of critical goods, 

• Efficient use of delivery fleets, 

• Optimal driver health and

• Increased customer satisfaction. 

Route optimization is thus one of the most important ways in which predictive analytics is driving last mile delivery solutions. 

Demand Forecasting

In a world where customers expect lightning-quick deliveries, forecasting demand is as important as optimizing routes. 

Say you are a mobile phone manufacturer, and you’re launching a new phone. Now, your inventory can’t exist equally across different geographical locations. This is because your customers themselves are spread unevenly. 

So, you must decide where your biggest inventory should be and how many units you should keep in which warehouses. Here, Predictive analytics is inevitable. 

Using factors like population density and purchasing power, predictive analytics can tell you: 

• How much inventory to distribute in different areas,

• Which warehouses to prioritize,

• How much time it will take to re-stock inventory, and

• The cost-benefit analysis of prioritizing key warehouses in different cities. 

This is an example of how logistic regression for predictive analytics can be used to pre-empt last mile delivery requirements. And once you know the requirements, you’ve already won half the battle! 

Inventory Management

Inventory management is downhill from predictive demand forecasting. 

Demand forecasting is necessary for specific seasons, such as festivals and sales, or events, such as product launches.

Inventory management, on the other hand, is important for fast-moving consumer goods with a year-long demand. 

Similar to demand forecasting, predictive analytics can use factors like historical demand for products, the rate of pilferage and the time required to replenish inventory to:

• Predict future demand trends, 

• Minimize the rate of pilferage, 

• Minimize overproduction,

• Determine the optimal time to replenish inventory,

• Pinpoint key warehouses can strengthen supply chains,

By calculating such metrics for managing inventory, predictive analytics can accelerate last-mile delivery operations while minimizing waste and costs.   

Predictive Maintenance 

The supply side of last-mile delivery comprises three characters: the drivers, the vehicles and the fleet managers. 

Of the three, the fleet managers are responsible for:

• Setting up delivery routes, 

• Optimizing schedules and 

• Maintaining asset and driver health. 

That’s where predictive maintenance comes in. It helps fleet managers look for patterns in historical and real-time data collected by Electronic Logging Devices and stored in cloud infrastructure. 

With predictive assistance, the fleet managers can ensure: 

• The routes are the fastest and the shortest possible ones, 

• The drivers have everything they need to meet delivery targets,

• The assets are well-oiled to ensure minimum downtime. 

Thus, predictive maintenance is one of the most effective ways of solving last mile delivery challenges in supply chain operations. 

Dynamic Delivery Scheduling

One of the great challenges of last-mile deliveries is missed deliveries. 

This often happens because a delivery requires a customer to be present at the delivery location. 

A missed delivery means poor resource utilization and a decrease in delivery efficiency. It also disrupts the flow of optimized delivery routes. 

By creating a delivery schedule based on customers’ personalized delivery preferences and past delivery records, predictive analytics can come up with dynamic delivery schedules that:

• Optimize delivery routes in real-time based on customer availability,

• Minimize missed or attempted deliveries, and

• Increase customer satisfaction through more convenient deliveries.

Additionally, predictive maintenance systems can also rely on customers’ answers about their availability while drawing up a delivery schedule. 

By focusing attention on small details, predictive maintenance can thus help reduce the costs of last-mile delivery while increasing customer satisfaction.  

Advanced Driving Assistance Systems

Advanced Driving Assistance Systems (ADAS) is a great example of the deployment of predictive analytics in logistics operations. 

By using historical driving patterns on specific routes, ADAS backed by predictive analytics can empower drivers with features like: 

• Collision avoidance and automatic breaking,

• Traffic signal recognition,

• Blind-spot detection,

• Automated parking,

• Traction and speed control on slippery surfaces,

• Following distance warnings and

• Lane driving assistance.

ADAS is the perfect manifestation of how predictive analytics solves last mile delivery problems, ensures driver safety, protects assets and optimizes routes—all in one go. 

End-to-End Fleet Maintenance 

Studies suggest that fleet downtime costs an average fleet between $480 to $760 every day! 

It is no wonder that fleet management is an industry worth a whopping $23.51 billion as of 2023. 

After all, who wants to lose $500 a day just due to asset downtime? 

The rising costs of fleet maintenance underscore the importance of predictive analytics in logistics operations. It helps you ensure that your vehicle is attended to in your warehouses rather than out on the road when it is loaded with inventory. 

And the use of predictive analytics is not just limited to maintenance. It also includes: 

• Energy and fuel management, 

• Fleet acquisition strategies, 

• Fleet insurance and risk management strategies, 

• Roadside assistance and accident management,

• Driver education, policies, testing and periodic health checkups,

• IoT and software integration through mobile and enterprise applications. 

Therefore, end-to-end fleet management is the best way to deploy predictive analytics in developing future-proof last mile delivery solutions. 

You May Also Like: 11 Cutting-Edge Fleet Management Technologies to Transform Your Logistics Business

Insider Tips on How to Leverage Predictive Analytics for Last-Mile Delivery

As a veteran logistics consultants, we would be remiss in our duties if we didn’t tell you how you can harness the power of predictive analysis in logistics for last-mile delivery operations. 

Here are the secrets to success: 

Use a Fleet Management Software

The ideal way of using predictive analytics is to use an end-to-end fleet management software. It utilizes logistic regression for predictive analysis and comes with a centralized control panel. It can help you: 

• Optimize routes, 

• Manage inventory, 

• Monitor asset health in real-time,

• Manage drivers and provide on-the-go assistance,

• Create maintenance schedules, 

• And clean up last-mile delivery operations. 

If you don’t want to invest in creating customized fleet management software, you can start by using freeware to explore its different features. 

Choose a Secure Cloud-Based Data Storage Option

Clean data is one of the foundations of using predictive analytics in logistics. 

So, you should start by choosing a robust cloud-based data storage option. 

This will protect your data and remove dependence on physical data infrastructure. It will also help you seamlessly collaborate with third-party enterprises that specialize in predictive analytics. 

Thus, it will ease your transition to last mile delivery solutions backed by predictive analytics. 

Create a Mobile App

A great way to optimize last-mile delivery operations is to empower your drivers with enterprise-centric mobile applications. 

A mobile app can help your drivers:

• Harness the power of ADAS infrastructure, 

• Get help during emergencies or troubleshoot vehicle problems and

• Communicate with fleet managers in case of route changes. 

Robust mobile app development services can help you fully utilize predictive analytics to solve last mile delivery problems. 

Additionally, a customized mobile app rather than a plug-and-play version will help you secure enterprise data and customer information with state-of-the-art security infrastructure. 

IoT Integration

Last but not least, we recommend that you integrate IoT devices into your last-mile delivery fleets to stay ahead of the curve. 

They’ll help you record the data that is vital for predictive analytics to work its magic. Some of these data points include historical route information, the number and specification of vehicles in your fleet, the fuel consumption of your vehicles and more. 

IoT tools like Electronic Logging Devices are almost a prerequisite to implementing predictive analytics in last-mile delivery logistics. 

How Green Apex Can Help You Optimize Last-Mile Delivery Operations?

Today, our collective production capacities are growing like never before. As a result, more and more products need robust supply chains to get them to the end user as quickly and efficiently as possible. 

In this ever-expanding logistics landscape, last-mile delivery is the last obstacle standing in the way of accelerated product delivery. 

At Green Apex, our mission is to harness the power of predictive analytics to develop creative solutions to the puzzle of last-mile delivery operations. 

From IoT integration to AI/ML-led software development, our veteran engineers stand ready to help you implement highly effective last-mile delivery solutions in your logistics operations. 

Through best-in-class mobile app development services, we can also equip your fleet managers and drivers with a sophisticated delivery application that increases delivery efficiency. 

Connect with our logistics consultants and discover how you can accelerate your last-mile operations, cut costs and increase customer satisfaction!