AI and machine learning are taking over more and more industries and aspects of our lives, and logistics is no exception. AI and machine learning in logistics can be a great help when it comes to the supply chain sphere. Using them, it is possible to optimize the processes, avoid mistakes which humans can make or miss, predict future opportunities and challenges.
Therefore, make the business itself more successful and profitable. Here are some more details regarding the benefits of implementing AI in the supply chain. So keep reading to discover how AI and Machine Learning algorithms can help your business to develop.
Supply chain planning using machine learning
Supply chain planning, or SCP, is among the most important activities included in SCM (supply chain management) strategy. Therefore, it is crucial to have reliable tools for developing efficient plans. If you implement machine learning, your supply chain decision-making processes can be optimized significantly. Analyzing huge data sets and applying intelligent algorithms, you and your team will balance demand and supply, and at the same time optimize the delivery processes.
Another great thing, apart from better supply decisions, is the fact that human intervention is minimal. You won’t have to analyze those loads of data on your own. Artificial Intelligence (AI) algorithms will do everything for you and save you from making mistakes. You will only have to set up the parameters.
Machine learning in logistics – Warehouse Management
Proper warehouse and inventory-based management is a must for efficient supply chain planning. Why? Well, because both over-and under-stocking can turn into a real challenge for your business and destroy even the most efficient SCP strategy. Machine learning and its forecasting feature can solve the problem and completely change your warehouse management for the better. And, again, artificial intelligence can analyze a big data set much faster than you will even be able to do, and easily avoid all the mistakes which humans can make.
Track and warehouse analysis
Computer Vision (CV) is a field of study which is responsible for developing diverse techniques that help computers to see and understand images and videos. And this is exactly that tool which can provide you with warehouse automation and solve a number of tasks. For instance, computer vision systems can automate the barcode reading process and, therefore, accelerate and simplify it.
They can also monitor the warehouse perimeter and track the employees, analyze the data, and prevent thefts and violation of the safety rules. And thanks to facial recognition technology, a computer vision system is also able to identify who is entering and leaving the warehouse territory.
AI in logistics for demand prediction
To improve your supply chain efficiency, you can use artificial intelligence and machine learning in order to predict the demand or improve the demand forecasting. In case you have already tried to do something like that. On the basis of the past experience, you will get a detailed analysis of all the factors which may have an influence on the demand. Using this knowledge, you will be able to make the right business decision.
And just like in many other cases, artificial intelligence and machine learning are much more effective than traditional methods of demand prediction. The thing is that those methods which you may be used to consider fewer demand-influencing factors. Thus, such predictions can’t be as reliable as those ones made with the help of advanced technology.
Logistics route optimization
To reduce the costs of shipping and make the shipping process itself faster, you can use artificial intelligence to decide on the best routes. This is especially important in case you are a large e-commerce company with a lot of customers. They are always happy to get their orders as soon as possible, without any delays. And artificial intelligence (AI) is what you need to analyze the existing routing, do the track route optimization. Therefore, you will be able to reach better results and bigger profits.
Predicting peak hours using AI in logistics centers
Artificial intelligence and machine learning are able to monitor and predict traffic and other factors which can somehow influence your shipping time. Peak hours in logistics centers are also an important factor, so we recommend you to use the technology to predict and, therefore, to avoid them. As a result, you will spend less time in the centers and make your customers happier.
Supplier selection and supplier relationship management
Selecting a reliable supplier and maintaining a proper relationship with them can be extremely challenging. If you make the wrong choice, your business can suffer, and the same can happen in case you make a mistake when managing your cooperation. In the worst case, your business can even fail.
But if you apply machine learning to the data sets based on your supplier relationship management actions (for instance, audits and credit scoring). You will get pretty reliable predictions for every interaction with your potential or already existing supplier. This trick will help you to avoid many mistakes and build a mutually beneficial collaboration.
Foreign language data cleansing and building data robustness
Natural Language Processing, or NLP, if short, is an element of machine learning and artificial intelligence (AI) domains which is a great solution when you have to decipher loads of foreign language data. In some cases, language barriers can be very hard to deal with.
As a result misunderstanding can lead to serious problems and inefficient business decisions. But with the help of NLP, you and your team will avoid the potential troubles and streamline those compliance and auditing actions which were unavailable before due to the language issues.
Workforce planning
Workforce planning is a must for any modern organization. It involves such processes as recruiting, retention, employee development, redeployment, performance management, and some others. Machine Learning and artificial intelligence (AI) solutions can significantly simplify them and make your workforce planning strategy more efficient.
Thanks to this, you will get a happier team. This is important, as employees who like their organization and the way of work are more productive. And with such a team, your business will become more successful.
Autonomous vehicles – AI in logistics and shipping
Logistics and shipping are pretty obvious things when talking about the supply. In most cases, goods have to be somehow delivered to the customer, contractor or whoever else. And here we have a lot of restrictions! For instance, drivers are allowed to drive non-stop only for a certain amount of time. After this, they have to take a break or be replaced by another driver. But having at least two drivers on every delivery truck can be expensive, while a need to wait until one driver will rejuvenate can significantly prolong the shipping time.
Both these issues can have a catastrophic impact on your business, especially in the modern world of severe competition. However, autonomous vehicles can solve these problems, and save your budget and time. The only thing here is that such vehicles are not advanced enough at the moment. So you will have to wait a bit. But as soon as they enter the market, don’t miss this opportunity. Autonomous vehicles are a great choice when it comes to shipping.
Drones used in the delivery
Delivery drones are one of the latest solutions that enable logistics companies to deliver products to the most difficult places. Companies often struggle to get their packages delivered to places where a ground transfer is not safe or reliable, and in some cases even impossible.
Drones have revolutionized delivery logistics, especially for companies such as pharmaceuticals, where products often have a short shelf life. Problematic transport often results in the waste of products or the need to invest in specialized warehouses, which are a significant expense.
The latest AI use cases
AI in Logistics: Marketing and sales departments
AI solutions play an important role in improving marketing processes in logistics companies. One of the many examples is email marketing. This usually time-consuming task can now be automated thanks to artificial intelligence. Now marketers can focus on more creative tasks while AI-based software takes care of repetitive tasks.
Chat bots – an AI in logistics solution that automates customer service
Every organization operating in logistics knows how much work it takes to offer high-quality customer service. Customers often expect companies to answer their questions and solve their problems immediately.
The delivery processes are complex and not fully predictable, so problems arise from time to time – that you can be sure of. How can you optimize customer service so it’s effective and cost-efficient?
The answer is chat bots. Chat bots for customer service can take over the most common call center tasks such as tracking shipments, delivery requests, reordering and answering frequently asked questions.
In addition, chat bots can analyze customer experiences and draw conclusions on how to improve them. Companies can now better understand their customers’ needs and respond to them immediately.
Dynamic pricing with AI in logistics
In short, dynamic pricing is advanced real-time pricing that responds to changes in supply and demand, as well as to changes in competitors’ prices and the prices of dependent products. As a result, companies can offer optimal prices for their products that will attract more customers.
How does dynamic pricing software work? It uses machine learning algorithms to analyze the customer’s historical data in real-time. This way, it can react faster to changes in demand and adjust product prices.
Damage detection
Nothing disappoints your customers like opening a new purchase only to find out it’s broken. This experience often leads to bad reviews and customer churn.
To prevent such situations, implement computer vision solutions to identify damages. This advanced technology will enable you to determine the damage depth, find out what type of damage it is, and make changes to prevent or at least reduce further damage.
Automation of back-office tasks
Nowadays, companies can automate many back-office tasks thanks to hyper automation.
Hyper automation can be achieved using a variety of technologies such as artificial intelligence, process mining, robotic process automation, and more.
Here is a list of some back-office tasks that you can automate for your business:
•Generating reports. Logistics companies can now automatically generate basic reports that are necessary to update managers and make sure every employee is aligned.
•Tracking and scheduling. Machine learning in logistics helps you organize cargo pipelines, create transport schedules, assign employees to different tasks and implement package tracking in the warehouse.
•E-mail processing. Process automation robots can analyze the content of automatically generated reports and send appropriate e-mails to stakeholders.
Wrapping up – AI in logistics
Companies face tremendous pressure to implement AI and machine learning to improve operational efficiency and streamline business decisions with futuristic systems. Advanced technologies can also help logistics businesses to provide the ability to optimize production, logistics, warehousing and final delivery at various levels.
AI in logistics improves customer experience. With machine learning-based solutions, your products will be delivered in perfect condition and on time. Additionally, your team will gain extra time and business insights that will help your management team make successful decisions and ensure the growth of your business.
Now you know how useful artificial intelligence (AI) and machine learning applications can be in logistics and supply chain management.
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