5 Interesting Ways in Which AI can Enhance Your Supply Chain
Artificial intelligence is gradually gaining a foothold as a mainstream technology in most industries. So, what is this technology all about? Artificial Intelligence is the intelligence displayed by machines, in which, learning and action-based capabilities mimic autonomy rather than process-oriented intelligence. Ideally, AI can be broken down into two categories- Augmentation (which assists humans with their day-to-day tasks) and Automation (which works completely autonomously in any field without the need for any human intervention). Understanding these categories of AI capacities is essential for the future implementation of artificial intelligence into business work tools. The application of AI into supply chain related-tasks holds high potential for boosting top-line and bottom-line value. Here are some interesting ways that artificial intelligence can help enhance your supply chain:
To streamline procurement and related tasks through automation and augmentation with the help of chatbots, there is a need for robust and intelligent data sets which the procurement bot would be able to access as a reference. Chatbots are a form of artificial intelligence that can be used for functions like speaking to suppliers, place purchasing requests, and also to set and send actions to suppliers regarding governance and compliance materials. With the help of these automated functions in the supply chain, a company can increase their focus on other vital areas.
Supply chain planning
For any business, supply chain planning forms a crucial aspect of the supply chain strategy. Machine learning coupled with supply chain planning could help companies in forecasting within inventory, demand, and supply. Machine learning also has the ability to revolutionize the agility and optimize supply chain decision-making. With the help of machine learning, supply chain managers can deliver the best possible outcomes based on intelligent algorithms and machine-to-machine analysis of big data sets.
Supply chain planning is heavily reliant on proper warehouse and inventory-based management. One of the main problems most businesses face regarding warehousing is understocking or overstocking. Machine learning algorithms and data streams have precise predictive power to forecast the supply and demand. With this mechanism, issues pertaining to the shortage or excess stock can be avoided.
Logistics and shipping
The rising demand for on-time delivery is putting pressure on companies to improve the efficiency of their shipping and logistics facilities. Efficiency in shipping and logistics is a win-win situation for both the company and its customers. Faster and more accurate shipping reduces lead times and transportation expenses, adds elements of environmental friendly operations, and reduces labor costs.
Choosing the right supplier and maintaining a good professional relationship with them is a crucial task for businesses. Also, sourcing from the right suppliers is an increasing concern for enhancing supply chain sustainability, CSR, and supply chain ethics. A single slip-up in this operation could lead to bad PR and negative publicity for a company. With the help of machine learning and intelligent algorithms, firms can get active real-time data about their suppliers. This will help them in better choosing the best supplier from the lot with minimum errors of judgment.