Overcoming the Challenges in Inventory Management Planning with AI

Demand predictions do not always go as planned. Sometimes, poor visibility in the supply chain could be a hurdle and that can cause unprecedented glitches in inventory management planning. Inventory issues can lead to huge losses for businesses and in the worst case. They can also cause production to come to a halt. To avoid all this, businesses now switch to the use of the latest technology like artificial intelligence (AI) in order to overcome common inventory management challenges. 

How can AI help businesses overcome inventory management challenges?

• Data mining for a more robust demand forecasting

Most often, demands for a particular product or service would be based on a combination of different factors some of which are interrelated. A few factors change erratically and others might only see periodic changes. Data mining with the help of AI-integrated systems makes it possible for businesses to garner data pertaining to different factors. The machine learning model incorporated can be programmed to capture multiple influential factors like market fluctuations. Seasonal trends and historical demand data. A cumulative prediction based on several such attributes will be a more dependable approach to demand forecast and thus better inventory management planning. 

• Use of IoT to avoid surplus in inventory

Too much stock can be a burden on the inventory. Input and output inventory both need to be stock just right. Excess goods can cause a strain in the controlled storage units and bring down the quality of storage of finished goods and raw materials alike. Internet of Things or IoT is a concept that helps in better labelling of products and real-time tracking. Every single product that moves through the supply chain will be clearly monitor until the warehouse picking process and delivery of finished goods. Using AI makes it possible to enhance warehouse management.

• Make delivery timelines easier to estimate

Timely deliveries are persuasive attributes that can change shopping behavior. When customers compare closely competing e-commerce sites, the delivery timelines and the assurance of timely deliveries might be deciding factors. Short delivery times would be important but what matters even more would be the assured delivery within the promised time. For estimating the time to deliver a product as well as eliminating hurdles in deliveries AI-can be a handy tech. Optimal routes for quicker deliveries can be calculate with databases that contain information about all the influencing factors. Along with this real-time inventory tracking ensures that the delivery promise is met. The biggest strength of AI in comparison with other data tracking and automation technologies is that AI models can be programs to learn and adapt from real-time feedback. For example, the first few orders can be based on the predictions provided by the model. Hurdles in deliveries based on predicted timelines and the possible enhancements to improve the process flow can then be fed into the system. Also, This helps in automatically adjusting the delivery estimates in a more realistic way. 

There are many more such benefits for businesses that choose to use AI for inventory management planning. It helps in long-term stock management and inventory replenishment processes as well. In short, a more resilient system would be in place with the incorporation of AI in inventory management.