Artificial intelligence (AI) applications using natural language processing for the supply chain can help global as well as local supply chains create better human-machine interfaces for not just customers but also suppliers, manufacturers, and distributors.
With continued globalization, supply chains across the world are only going to get larger and more complex. Enterprises are increasingly taking the specialization approach, where all peripheral operations and business units are divested to increase the organizations’ focus on their main offerings by outsourcing these operations to overseas partners. As a simplified example of this, a toothpaste manufacturer who also makes their own toothpaste tubes can outsource the tube-making part of their operations to another business that specializes in it. This way, every organization is doing what it is best at with maximum efficiency. However, the rapid expansion of supply chains, while providing solutions to many problems, is spawning a few challenges inherent to supply chains. An example of these challenges is the language barrier that must be overcome by cross-border and cross-continent partners. These and similar barriers are being overcome with the use of increasingly advanced information and communication technologies. The applications of technologies such as AI and deep learning-based natural language processing for the supply chain is making supply chain operations simpler and more coordinated.
Applications of Natural Language Generation for the Supply Chain
Natural language processing can help people involved in the supply chain to understand normal human communications and process information faster to drive appropriate action. Following are a few ways in which natural language generation is employed in supply chains:
Facilitating Procurement with Chatbots
Manufacturing enterprises often deal with numerous suppliers for different components from different places. This makes the procurement process for components and resources complicated for these organizations, as they have to go through the hassle of individually sifting through supplier information for finding the suppliers who have what they need in the right quantities and can deliver within the desired timeline. To overcome this challenge and to facilitate the procurement process, businesses can use chatbots to interact with supply chain personnel and help them with the procurement process. They can interact with the chatbots that can gather requirements by conversing in natural language from any region, making the process easier for even those with minimal technical know-how.
Improving Customer Interactions
Applications of natural language processing for the supply chain also improve customer-facing applications such as using customer service chatbots. These chatbots can interact with customers to gather their requirements can generate order forms and instructions for the suppliers, manufacturers, or distributors. This can not only minimize the manpower required to process orders but also eliminate the possibility of errors in order information.
Gathering and Structuring Data for Analytics
Big data analytics has become indispensable to the modern enterprise. However, most data that can be utilized to create actionable insights is available in an unstructured format, often in the form of natural language text. The use of natural language processing can help analytics tools to make sense of such information and glean valuable insights. These insights can help in driving greater operational performance.
As the technology continues to mature and become more functional, the applications of natural language processing for the supply chain will gain greater importance. With the help of technologies like computer vision and augmented reality, supply chain operations can become even simpler for the employees and efficient for the owners.
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