How can logistics and supply chain benefit from data science? That’s the question that we want to focus on in this article. In the modern retail world, data science is literally everywhere. Smart solutions help companies track their parcels, manage supply chains, pave the way for autonomous trucks and autonomous delivery solutions, and even develop intelligent self-service stores. If you operate in the logistics sector, sit back because you’re about to change your thinking about the industry you work in!
The logistics industry is one of these branches of business that usually remain unnoticeable to ordinary Joes. However, there’s quite a lot going on in this vital sector of business.
- According to the International Chamber of Shipping, there are more than 50,000 merchant ships operating in the oceans currently.
- According to Science on a Sphere, on any given day, more than 87,000 flights are in the skies in the United States. One-third are commercial carriers.
- As TruckInfo estimates, there are over 15 million trucks in the US alone. And it doesn’t matter what aspect or sector of the logistics industry you have in mind. Almost every single one of them can be improved, optimized, and accelerated with data science in logistics and supply chain. And in this article, we want to show you some of the most interesting examples of such applications.
If you find this topic interesting, try reading our case study Machine Learning, Predictive Analytics and Data Integration in Logistics.
Data science in logistics and supply chains
DATA SCIENCE IN INVENTORY MANAGEMENT
Inventory management is a critical aspect of everyday work in every e-commerce and retail company. And since inventory is strictly dependent on logistics efficiency, let’s start here. Consider large retail/e-commerce companies like Walmart or Amazon. They have tens of warehouses spread across the whole country or even the world. And on top of that, these companies sell, pack, and ship thousands of products daily!
In such a demanding environment, impeccable inventory management is a must. And this is where data science comes into play. You see, more and more often, retail companies look for intelligent solutions to improve their inventory management processes. The vast majority of these smart solutions are based on data science and artificial intelligence. With data science, every retail and logistics company can:
- Optimize stock levels
- Shorten and optimize inventory management processes
- Prevent the dead stock issue (a word of explanation: Dead stock is a logistics term that relates to products that are outdated and unattractive to customers so that eventually they become unsellable)
- Improve CX
The very first example of a company that harnesses data science in their inventory processes is Amazon. We all know that it’s an e-commerce behemoth, but did you know that in 2012 they purchased a robotics company called Kiva Systems? Shortly after, they created Amazon Robotics, a division that builds mobile robotic fulfillment systems and bots. As a result, there are tens of thousands of robots working in Amazon warehouses today. They have one purpose–to automate inventory management and preparing orders for shipment. Their precision and efficiency are breathtaking. Take a look at this video that shows Amazon Robotics in action:
And here’s another fascinating example of intelligent data-driven solutions in action. Lowe’s is an American home improvement retail company. Recently, they’ve introduced LoweBots. These autonomous assistants move around their stores and, in case a customer needs help, show them the way to their desired products or even take them there. But there’s more to LoweBots than that. Their second objective is to monitor inventory in Lowe’s stores constantly. As they move around, they scan shelves and sections in the store and inform of product shortages. Again, let’s watch a short video:
Not far from autonomous inventory management bots lies autonomous delivery. And first off, let’s talk about the concept itself. Actually, it’s a perfect covid-proof solution! Imagine autonomous bots that deliver your online orders straight to your doorstep. There’s no driver or courier so there’s no direct contact with another person. Such bots could work 24/7 and arrive at your home when you are back from work. Sounds good, doesn’t it?
The good news is, we’re not talking here about some imaginative concept. Autonomous delivery bots already exist! Again, let’s go back to Amazon. They have a whole fleet of so-called Scout robots. And these robots are already delivering packages in selected suburban areas in the United States. Take a look at how Scout robots work in real life:
Obviously, Amazon is not the only company working on this solution. Another example is Starship Technologies. They started only in 2014 and, since then, they completed over 1,000,000 autonomous deliveries! Starship bots, just like Amazon’s, can navigate around people and public spaces without a human driver. They even look similar. Starship bots work primarily at universities and campuses, but just wait and see how popular they will be in the coming years!
When it comes to the logistics industry, autonomous vehicles can be a huge milestone. The reasons are apparent:
- They save time and money
- The number of accidents decreases
- They can operate 24/7, all year round
Of course, this is still a project in the making, primarily due to legal regulations which forbid autonomous vehicles from driving on public roads, but the fact is autonomous vehicles are already here, and they’re here to stay!
Consider Waymo. It’s a US-based company that began as the Google self-driving car project back in 2009. Today, they are working on the world’s first autonomous ride-hailing service and autonomous trucking and local delivery solutions. Unlike Starship, Waymo works on autonomous driver systems that can replace the human driver in normal cars and trucks. Currently, their main focus is on integrating taxi services with self-driving cars. Waymo system uses lidars, cameras, and radars to maneuver in real-world conditions effectively. They’ve already tested this system in over ten states when they have driven millions of miles on public roads and billions more on simulations.
Now, imagine a warehouse where data-driven solutions and assistants help you with:
- Inventory management
- Demand forecasting
- Quality assurance
They are so-called smart warehouses. Even people working there are equipped with data-driven wearables that facilitate their everyday work. With these wearables, warehouse workers don’t have to waste time figuring out where the specific parcel or order should go. Everything happens instantly with automated picking systems. A good example of such a system is pick-to-light. This picking method is based on hand barcode scanners and LEDs attached to shelves in a warehouse. The worker scans barcodes on the boxes. Depending on what should be included in a particular box, the barcode scanner displays a specific color. The worker’s role is to follow the LEDs displaying the same color and collect the products they indicate. Quick and efficient.
But smart warehouses are so much more! Consider British grocery store Ocado. Ocado uses data science and artificial intelligence to manage their warehouses. Warehouse workers are supported by bots that sort, arrange goods, and supervise stock levels. The automation of these activities allowed for a radical reduction in the time spent on organizing goods and processing orders in Ocado’s warehouse. The new Ocado warehouse has thousands of robots that automatically pack customers’ orders. Every week, Ocado bots handle up to 65,000 orders. They communicate over 4G networks to avoid bumping into each other. Here’s what it looks like:
INTELLIGENT SELF-SERVICE STORES
Yes, we know that self-service stores don’t have all that much in common with the logistics industry, but from the retail standpoint, it’s a vital trend that will surely thrive in the coming years, affecting the logistics sector as well. And here, we have to go back to Amazon for the third time today. As it happens, Amazon runs Go stores. These are 100% self-service stores with no human workers. Here’s how they work:
- A customer needs to have an Amazon account and an app.
- They scan the app at the entrance to the store
- Do their shopping
- And leave the store
Now, what happens in the meantime? Amazon stores are fully data-driven. This means that they are packed with AI-related technology, primarily deep learning, and computer vision. The cameras and sensors located in the Go stores detect when a customer starts shopping, scan their cart, and detect when they walk out. In fact, every customer and their activity in the store is continuously monitored. And when they leave the store, their Amazon account is automatically charged for the purchases. You simply have to see Go store in action:
The Internet of Things and blockchain in logistics and supply chain
At this point, we also want to show you three examples of companies that leverage AI-related technologies, primarily IoT, but also blockchain in order to improve global logistics and supply chains.
In early 2019, IBM published a piece of information about the new project of Golden State Foods. Interestingly, they decided to concentrate on the supply chain related to… beef. The fact is, Americans simply love beef, and Golden State Foods wanted to show their customers the entire production process of one of their favorite foods. Actually, the beef-related supply chain can be difficult to comprehend. After all, long before a delicious, freshly-fried hamburger lands on your plate in a restaurant, at least half a dozen businesses are involved, including:
- Distribution centers
These companies take part in the entire logistics and supply chain process. Now, what Golden State Foods really did? They installed sensors at the distribution center. These sensors (also referred to as readers) automatically register the number of cases of beef leaving the given facility and send that information across the supply chain in real-time. To make everything even more transparent, restaurants can check that data via a dedicated dashboard. It presents information about where the shipments had gone, the temperature at which they’d been maintained, and their shelf life. And due to blockchain’s immutable nature, no one could alter the numbers, so GSF partners can rest assured that the data they receive is correct and accurate.
From America, we go straight to Asia to talk about another blockchain-based endeavor. VeChain is a blockchain company based in Singapore. Currently, they are building a decentralized platform for business solutions. With this platform, various companies participating in the same supply chain can easily interact and transact without an intermediary. In other words, VeChain makes it straightforward and safe for manufacturers to share product data with their vendors. For example, VeChain produces RFID chips (based on radio-frequency identification) and works on several upgrades for the technology, such as integrated thermometers. Such a solution will be capable of constantly monitoring the surrounding temperature of the food when it’s being transported, making sure it’s appropriate and safe for the specific product.
According to the company, Ambrosus is a leading blockchain protocol used for decentralized applications, securing the IoT, physically tracking real-world assets, and integrating blockchain into enterprise software. Ambrosus concentrates on two industries: food and pharma. They are working on a tracking system, which is essentially a combination of IoT sensors that can track movement, temperature, and other parameters across the entire supply chain. This company, just like VeChain, uses RFID chips, tokens, and QR codes to gather and process data that’s next being uploaded to the blockchain network for security purposes. When all of that is done, Ambrosus is ready to share it among counterparties.
It’s time to sum up. As you can see, data science in logistics and supply chain is an unexpectedly broad subject that covers almost every aspect of the logistics, retail, and e-commerce sectors. Soon, we can expect to see many more applications of data-driven technologies, mostly because in the COVID-19 times, both customers and retailers look for efficient, safe, contactless, and quick solutions that will allow them to grow sales.
If you run a logistics or retail company and you’re interested in how data science can help you in your work–feel free to drop us a line! At Addepto, we frequently work with retail and e-commerce companies enabling them to start utilizing data science and data-driven solutions. In many instances, the result goes beyond anything they have ever conceived!
 Marine Insight, Top 10 World’s Largest Container Ships In 2021, March 5, 2021, https://www.marineinsight.com/know-more/top-10-worlds-largest-container-ships-in-2019/ accessed May 17, 2021
 Science on a Sphere, Air Traffic, https://sos.noaa.gov/datasets/air-traffic/, accessed May 17, 2021
 TruckInfo, Trucking Statistics, https://www.truckinfo.net/trucking/stats.htm, accessed May 17, 2021