What Use Can Logistics Companies Make of the AI and IoT Technology Today?
Since the beginning of the new millennium, when technologies have become capable of replacing people in many complex, smart operations, more and more businesses realize the necessity to optimize their daily processes by digitalizing nearly every step in their performance. As I am focusing on logistics, I will give you a few examples of the use that logistics companies can make of the technology innovations today.
Logistics is changing these days. Technology has penetrated into all of its domains and changed the way how freight, sales orders, materials, goods, production, inventory and accounting are managed.
Every logistics company, however, performs its own, unique combination of specific operations that aren’t fully covered by ready-made solutions. This is why owners of logistics companies often have to decide whether to adopt a commercial solution or to invest into creation of software which would be tailored to their specific needs (so-called custom, or customized, solution).
Gartner has predicted that 50% of the large global companies will use advanced analytics, IoT and AI in their supply chain operations in 2020, and it seems they already do. Let us take a look at how the most innovative technologies like AI (artificial intelligence) and the newest IoT (Internet of Things) solutions work to the advantage of logistics companies. First of all, it is necessary to say that Logistics and Transportation Management (TM) system require continuous analysis of all operations and so every business has to attract logistics professionals who focus on the procurement and planning of transportation of people, goods or materials.
There are eight major areas to deal with in Transportation Management System: in each of them, the use of innovative technologies can boost the business and help companies overcome competition.
Dealing with Pickup and Delivery Requests
Here, a customer assigns pickup/delivery requests that go to the carrier. In this business, a great answer to optimizing daily operations would be to develop an interface for customers to send pickup/delivery requests. To handle the operations effectively, there are many logistics software available in the market. NetSuite and McLeod are popular platforms for logistics operations that are capable of doing many operations like forecasting and budgeting, supply chain and inventory, revenue management, customer relationship management and business intelligence. Companies that would like to make sure that all of their unique operations are covered may decide to develop their own software which will be adapted specifically to their needs.
Dealing with Carrier Management
How can carriers identify if the deliveries are done efficiently or not? The best answer to this task in the 21-st century is predictive analytics. Predictive analytics algorithms can ensure so-called on-time and in-full delivery, meaning that that fleets arrive on time, and goods are received and moved on time so that shipments are delivered to customers when they want it.
To make this possible, some IoT devices (sensors) are embedded in trucks, trains or ships; they feed data like engine performance, speed (or weight, temperature, humidity – literally any countable data) and send it to the carriers. Based on the received data, logistics specialists can model and predict the estimated arrival times and engine failures. For example, telematics data captured from a vehicle can reveal its speed, position, condition and time left to reach the destination.
The obtained data is also used to notify people about delays along with the load/unload activities, trucks heading to the same destination and product delivery requirements. As a result, all this ensures minimized delays and fulfilled customer expectations.
Smart logistics that uses AI and IoT can help ports, shipping companies, suppliers and agents optimize resource utilization and their schedules.
Another answer to the tasks of logistics is Demand Forecasting – a technology that works in the basis of inventory and orders data. Using it, companies can predict the demand for shipments and products in their supply chain. Logistics companies need to evaluate capacity demand based on the combination of historical data, including inventory data and order data. They implement forecasting models for better decision making. Companies that use custom demand forecasting models, obtain accurate forecasts that help them decide what additional capacity is required, how to routes and times of transportation, and what to do to improve cargo vehicle capacity and asset utilization.
Thanks to accurate predictions of asset and shipment demands, the logistics companies can increase cargo capacity and high-demand goods can be delivered to customers on-time.
Implementing IoT sensors in logistics makes tracking of goods more accessible. Sensors are used to capture and exchange data. IoT allows handling data remotely across the network infrastructure. Sensors can be embedded, for example, in vehicles carrying goods from one place to another. Data captured by sensors can be converted into valuable insights using AI. AI-enabled analytics facilitate tracking of shipments and send tracking reports during the trip. Real-time monitoring of goods provides information like departure and arrival times; loss of goods during the journey; live location of the shipment; any deviations from the scheduled route, etc. With all this information, logistics companies can considerably improve their operations.
In food transportation logistics, IoT sensors can be used to send useful data about food around the whole supply chain, ensuring that all food safety regulations are met and maintaining complete transparency of every operation.
Carriers are always interested in optimizing transportation routes and communication with warehouses, and here the role of IoT and AI technologies cannot be overestimated. IoT provides real-time insights that can be monitored and reported, therefore it becomes easier to identify and deal with delays due to weather conditions or maintenance issues with trucks, and carriers can be effectively traced throughout the whole supply chain.
Optimized route planning using AI and IoT is becoming a norm, even a necessity, for logistics companies today. Loads can be assigned for pickup to drivers based on their current location: a driver nearby can pick up a load and deliver it to a certain place. Depending on the type of goods to pick up, decisions about transportation can be made right ‘on the go’ due to the information captured by sensors and sent to the service providers.
IoT sensors can provide information on the type of goods, their real time location, changes of the planned route, delivery/pickup from warehouses, temperature, humidity, etc. If AI technologies are also implemented, the providers of logistics services can, for example, estimate delivery times, analyze driver’s behavior, check quality and condition of the transported goods, suggest solutions about the best routes to choose, etc. Thus, warehouses can efficiently plan their operations and do it in advance, which helps optimize the whole chain of the performed operations.
Pickup Optimization
Technologies, including AI and IoT, are used for pickup optimization. As trucks are selected for pickup based on the type of load to be carried, AI learns historical patterns of the previous operations and suggests the most efficient decisions to carriers. An AI-based model can predict which truck should picking up goods at a certain time in a certain place. If a truck is supplied with certain IoT sensors/devices, it is possible to gather information about the temperature under which goods are stored, the real time of the goods location, truck information like speed, fuel expenses, etc.
Warehouse Management
Certain combination of AI and IoT can facilitate carrier and warehouse collaboration. For example, IoT sensors equipped in a truck send the real-time location of the truck and its ETA to warehouse managers. Based on this information, warehouse managers can keep the required space vacant and prepare for the unloading of goods before time. It will help warehouses manage their schedules efficiently and precisely.
If sensors are installed around the warehouse area, they would send the information related to doors near the vacant space to truck drivers based on their GPS data and estimated time of arrival. It will help truck drivers reduce the time of entering the warehouse. And this is only one example of possible ways to facilitate better collaboration between logistics companies and warehouses.
IoT can be used to ensure safety of drivers and goods : specially designed locks facilitate interlocking of the trailer’s air brakes with the dock door. Smart locks ensure that the truck cannot depart until unloading/loading gets completed. Trailers can only leave the warehouse when the dock door is closed. It can keep your equipment and employees safe.
One more way to ensure the security of the warehouse is by using computer vision. IoT cameras can be installed in the warehouse area that captures the status of loading /unloading and load transfer. Edge computing can be applied to the smart cameras that enable the crucial action based on any event fetched during load transfer activity. If any fragile good gets broken up during unloading due to the bad behavior of labor, warehouse managers can get notified about it.
Transit Operations Optimization
IoT-enabled sensors and AI technology in combination with GPS sensors installed in trucks can provide its real-time location based on which AI model evaluates the estimated time of arrival. Based on the real-time data gathered by IoT devices, logistics companies can track transit operations in real-time.
With the help of predictive analytics companies study the difference between predicted time and the actual time the truck takes to reach the destination. Customers and logistics companies can know if the goods are delivered under the right temperature conditions.
Load Exchange Optimization
When a truck gets overloaded or gets into an accident, truck drivers have to wait for a long time to find alternative options. But IoT and AI can help reduce the wait time by capturing real-time data and enabling intelligent actions. AI-based models for load exchange optimization would allow quick exchange of load from one truck to another. IoT sensors would capture the information about the delay of the truck and a new vehicle will be assigned automatically to exchange the load and deliver it to the final destination. GPS devices installed in the truck provide information, including latitude and longitude, real-time location of the vehicle and motion of the vehicle. So, carriers can quickly determine the condition of a vehicle during an accident and react accordingly.
Delivery Process Management
To deliver goods from warehouses to end customers, trucks can be notified about the vacant door for picking up goods and warehouse operators would be informed about the load preparation. Then, the goods will be transferred to the carrier under the complete security using IoT-enabled locks and computer vision-based cameras. Once the loading is done, the carrier can set on the way and deliver the load to the customers.
Business Intelligence and Reporting
Once transportation operations are done, companies often need a comprehensive report that contain the negative and positive trends of performance during the supply of goods. Everyone knows that the demand for business intelligence within the logistics and transportation space is skyrocketing. They want to identify root causes and analyze negative trends in performance and cost to take intelligent actions.
Business Intelligence allows converting data into valuable information. Earlier, reporting was only limited to extracting data, fetching it from a system and bringing it into a spreadsheet or database where a company would try to use it and convert it into useful data.
But nowadays, business intelligence has reached the next level, where companies can generate valuable reports that showcase all the data about logistics providers in a scorecard format. Factors, including on-time pick-up and delivery, capacity commitments and driver behavior are assigned metrics that help users determine the performance of carriers.
Also, managers who require a daily and quick overview of what is happening can use real-time dashboards that provide real-time information and help users solve problems as they occur. Dashboards offer companies the advantage of quick reaction time as users don’t have to wait for someone to create and send reports.
Companies use BI and reporting to display patterns found in historical data that can predict opportunities and future risks in the supply chain or transportation networks.
Let’s understand how shippers can use business intelligence to improve logistics and supply chain operations with an example.
Suppose one shipper has a 90-percent on-time delivery rate for load transfer consistently, but he wants to go to the root of the problem dragging down the other ten percent of shipment. Did delays occur because of the broken lanes? Is there any problem with the equipment or carrier?
With business intelligence, it becomes possible to narrow down delay-causing factors. For example, if the shipper reached late due to the congestion in that way, companies can discover the issue with business intelligence and take necessary actions.
With BI data, it becomes easier for logistics companies and their team to make operational decisions more efficiently.
Therefore, implementing BI across the shipments can result in an end-to-end pickup and delivery time improvement.
Artificial Intelligence and the Internet of Things are disrupting logistics and transportation management by making logistics operations more smarter day by day. It is expected that delays in pickups/deliveries and trucking capacity concerns will become a matter of the past when AI and IoT come into use everywhere.
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