How logistics automation can multiply your business

How logistics automation can multiply your business

How logistics automation can multiply your business PlatoBlockchain Data Intelligence. Vertical Search. Ai.

Logistics plays a critical role in the supply chain of businesses of all sizes. It involves coordinating the movement and storage of goods, services, and information in a way that maximizes efficiency and minimizes costs.

Managing logistics, however, can be a complex and time-consuming task, especially for businesses that rely on manual processes. Tasks such as data entry and document processing can also be prone to errors, which can lead to losses, delays, and other issues in the supply chain.

This is where logistics automation comes in. By using technology to automate various tasks in the logistics process, businesses can significantly improve efficiency and accuracy, reduce costs and errors, and enhance customer satisfaction.

In this article, we’ll introduce you to logistics automation and how it can benefit your business. We’ll also dive into how Nanonets can help you automate various tasks in your logistics processes.

Overview of Logistics Automation

Logistics automation refers to the use of technology in the logistics process. These tasks can include data entry, document processing, shipping label recognition, inventory management, transportation management, warehousing, tracking and tracing of shipments, customs clearance, payment processes, and more. The goal of logistics automation is to improve efficiency and accuracy in logistics operations, enable data-driven decision-making, reduce costs and errors, and enhance customer satisfaction.

There are a number of different technologies that can help businesses automate various tasks in the logistics process. These can include:

  • Robotic process automation (RPA): RPA is a type of software that can be programmed to perform tasks such as data entry, document processing, and other repetitive tasks. RPA can help businesses automate these tasks quickly and easily, without the need for complex programming.
  • Artificial intelligence (AI) and machine learning: AI and machine learning can be used to automate tasks such as demand forecasting and inventory management. These technologies can analyze data and make predictions or recommendations that can help businesses optimize their logistics processes.
  • Optical character recognition (OCR): OCR is a technology that uses machine learning algorithms to extract data from scanned documents and images. OCR can be used to automate tasks such as data entry, document processing, shipping label recognition, and more.

Benefits of Logistics Automation

According to a study by McKinsey & Company, AI-enabled supply-chain management has enabled early adopters to improve logistics costs by 15 percent, inventory levels by 35 percent, and service levels by 65 percent, compared with slower-moving competitors.

Broadly, the benefits of logistics automation include:

  • Improved efficiency: Automating tasks such as data entry and document processing can significantly reduce the time, effort, and manual errors that tend to be routine to these tasks. This can free up resources that help businesses focus on other important tasks.
  • Improved accuracy: Automating tasks can help minimize the risk of errors, such as misinterpreting information or transposing numbers. This can improve the accuracy of the logistics process and reduce the risk of losses, delays and other issues.
  • Reduced costs: Automating tasks can help reduce labor costs and other expenses associated with manual processes. This can lead to cost savings for businesses.
  • Enhanced customer satisfaction: By streamlining the logistics process, businesses can improve delivery times and other aspects of customer service. This can lead to enhanced customer satisfaction and loyalty.

OCR and Nanonets for Logistics Automation

Nanonets is a machine learning-based OCR platform that can help businesses automate various tasks in the logistics process. It offers an API for integrating with logistics systems, as well as a user-friendly interface for training and deploying machine learning models.

Some specific use cases for Nanonets in logistics automation include:

  • Extracting data from invoices and purchase orders: Nanonets can be used to automate the process of extracting data from invoices and purchase orders, such as item descriptions and quantities. This can help businesses accurately track their inventory and expenses.
  • Automating shipping label recognition: Nanonets can be used to automate the process of extracting data from shipping labels, such as tracking numbers and recipient information. This can help streamline the shipping process and reduce the risk of errors.
  • Classifying and routing incoming documents: Nanonets can be used to classify and route incoming documents, such as invoices and purchase orders, based on predetermined criteria. This can help businesses efficiently process and organize these documents.

Takeaway

Technology has brought many innovations to the logistics sector, and embracing these have become the cost of doing business today. While there are several logistics automation systems to invest in, the easiest and most affordable way to start is the automation of the data entry process. This itself can help save time and reduce errors, improving customer satisfaction.

With Nanonets, you can pull and manipulate data from documents seamlessly.

Time Stamp:

More from AI & Machine Learning