55% of business leaders in supply chain and top bosses in finance plan to invest in Artificial Intelligence in the next couple of years according to a recent Forrester survey. This stat tells us AI is increasingly being seen as a technology capable of driving effective decision making and improving operational processes.
Here are 4 ways AI can catalyze improvements in supply chains:
1. Automation of Repetitive Manual Work
Recognizing regularly occurring patterns lies at the very core of machine learning. This can be leveraged for repetitive manual tasks that include inspection of outbound and inbound deliveries, quality control of products, damage identification and more. The use of AI can ensure these tasks are handled seamlessly, quickly and with a greater degree of consistency as compared to manual workers. Over the long term, AI can actually reduce costs associated with such activities, thus bringing down overhead.
2. Inventory Management
Maintaining stock levels and optimizing stock distribution is the foundation of effective supply chain management. Integrating machine learning with more IoT sensors will help offer granular information of the location for every stock item and also inform whether it’s a return or repair, in a warehouse, on a store shelf, or an outgoing order in transit.
But this is not all; AI can also give you comprehensive insights into associated data such as storing costs at different locations; this helps you reroute and distribute stock in the most efficient manner possible. Companies can experience immense financial benefits by maintaining optimal stock levels to satisfy demand and also enhance reverse logistics.
3. Customer- and Partner-Centric Chatbots
According to IBM, businesses receive 265 billion customer service calls that cost $1.3 trillion every year. These calls include routine calls that can be answered by chatbots. With customers wanting to be on top of the order processing cycle and using diverse communication channels to keep in touch with suppliers, chatbots can come in to handle predictable queries. This not only can help speed up response times but also frees up agents to deal with more important and complex queries.
The use of AI, in this case, will save time, increase productivity and reduce costs. The machine learning foundation of these chatbots ensures they identify patterns and can improve on the job. The information chatbots gather can be used to identify a problem area and address issues.
4. Automating problem solving
Automated decision making for solving commonly occurring problems is one of the critical ways supply chains can be transformed with AI. For example, many suppliers have to deal with huge gaps in processes that impede end-to-end supply chain visibility and control when it comes to managing customer orders. Using AI, suppliers can gain better visibility and control with the help of a control tower to implement specific acceptable parameters with respect to the cost of individual orders, delivery time and various other constraints.
This ensures problems can be addressed automatically, for example, in case an order reroute is required because of a problem, AI can automate this process if it falls under the set parameters drawn up earlier; problems can be addressed in real time.
There are plenty of benefits AI brings to the table for supply chains. Each benefit leads to tangible cost savings, improved productivity and seamless operations. It’s time organizations start using AI to improve their supply chains.