Barcelona, September 13, 2022.- The company SoulPage has published a report on the functionalities of Artificial Intelligence in companies that are experts in the supply chain. These are the conclusions:
The main objective of any supply chain remains to be the management of inventory, from procurement to supplying the right product at the right time in the right place. And, for traditional supply chain companies, it has always been a challenge to achieve it as they focus majorly on optimizing a particular segment of the supply chain, rather than optimizing the entire value chain. This limits their operational efficiency to meet the need for granularity in customers’ unique expectations. Artificial Intelligence (AI) can help supply chain companies in breaking the silos to reinvent their operational models. AI in the supply chain helps companies in procuring and processing large datasets and provides better visibility within the supply chain.
57% of the companies across the world believe that supply chain automation can provide a competitive edge as applications of AI can resolve problems like inventory planning, supply network planning, production planning, etc. With advanced applications of technologies, 25% of the companies can solve their bottlenecks in forecasting supply and demand through data-driven insights by adapting and implementing AI and big data.
Companies are utilizing an optimized value network system and decision support system, as traditional practices in supply chain management, to decrease supply chain cost and optimize inventory. The applications of AI can provide optimal solutions in a decision support system. By conquering problems like product tracking and tracing in the warehouse, automated inventory management, rising supply chain management system cost, quality inspection, and elimination of defected products.
AI Applications in Supply Chain
AI has taken up the space to fill the gap in supply chain management for smooth business operations. Applications of AI technologies in supply chain management enhance the performance and increase the productivity of the business. This section describes a few applications of AI in supply chain management.
Predictive Analysis For Logistics Management
Companies are becoming more proactive as the application of predictive analytic tools can help in forecasting advanced information regarding customer trends and demand analysis. Hence a future analysis of demand and supply helps the supply chain management system in planning, the procurement of raw materials, inventory control, new product development, and supply analysis of finished goods accordingly.
Inventory assorting is the biggest task in supply chain management. It is crucial because the information regarding stock availability is recorded based on assorted inventory. Assorting is a time-consuming process and there is always a risk of human errors. Automated robots having advanced computer vision can scan images with a high accuracy rate to provide accurate information and reduce the cost of supply chain and human errors.
Chatbots provide efficient customer service assistance. The usage of AI chatbots in supply chains will have a similar output. The chatbot system can help the business entity in procurement analysis and inventory control.
Chyme is a chatbot assistant, used by salesforce and Australia’s largest beverage selling company, Carlton united breweries. While salesforce uses the chatbots for customer assistance, the Carlton uses the chatbots for client engagement and inventory control management. The chatbots provide instant information regarding procurement analysis, stock inputs, stock analysis, shipment status, and information regarding other queries. These help the employees in utilizing their time optimally.
Automated Quality Inspection
An automated quality inspection provides an advantage over manual methods used for inspection at logistics hubs. With automated quality inspection, the robot system programmed with computer vision, object detection, and machine learning algorithms, scans products in a three-dimensional view that detects faulty products at the ¼th time of human inspection.
Esyncronised supply chain
To facilitate and coordinate supply chain activities, the supply chain firms always transfer information regarding predictive analytics reports, demand forecasting, distribution channels, and joint distribution through web-based systems or electronically. Using web mining, and data mining tools, the data can be decoded and analyzed to recognize known and unknown patterns. This data, when further processed, will be helpful for other industrialists to know customer profiles, supplier profiles, demand fluctuations, sales trends, and sourcing trends on other websites.