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Technology in logistics through machine learning brings a series of benefits to optimize operations, reduce costs, and promote innovation. Artificial intelligence, big data, and machine learning are some of the trending terms and concepts today. Different sectors have adopted technology as their main source of information and driver of their work. In logistics, it couldn't be any different. Today, technology in logistics has been fundamental for the optimization of many operations and, consequently, their success. One of the main tools for this is machine learning. This is the subject we will cover in this article, understanding what this concept is and how it has helped in market growth. Happy reading! READ MORE • Artificial Intelligence brings efficiency to counting processes
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What is machine learning?
Machine learning is an artificial intelligence that is built from a database. It is based on the idea that systems and software can learn from data, identify patterns, and make decisions without relying on human interference. Thanks to new technologies, machine learning has evolved increasingly and gained greater importance within various segments and markets. Some examples of applications of this artificial intelligence are: • Autonomous cars
• Recommended offers in e-commerce
• Social listening, which is the monitoring of what is being said about your brand on social media
• Fraud detection in different processes
• Demand forecasting, route planning, and delivery performance in logistics
What is the importance for logistics?
Daily, the logistics sector needs to follow a series of activities. Forecasting demands, managing inventory, carrying out the distribution of goods and their transport, among others. Executing each of these steps requires attention and care to avoid bottlenecks that will harm the entire chain and generate much larger problems. It is, at this moment, that the importance of technology in logistics comes in through machine learning. Data analysis allows systems to perform various tasks autonomously, ensuring more agility to processes. Machine learning not only makes the chain more agile, but brings a series of other advantages, such as:
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Increased productivity
Ensures that processes are automated and agile, without the need for manual labor.
Reduction of error rates
The more data collected and processes carried out, the greater the systems' intelligence becomes when executing the task.
Less waste and costs
One of the main expenses occurs with rework after errors during processes. When these occurrences are reduced, costs end up falling. In addition to having the entire process more organized and scheduled, optimizing the spending of resources.
Increases customer satisfaction
This is a consequence of the previous points. With technology in logistics, you gain more trust at all ends, deliver a quality service, and satisfy your customer's needs.
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
