How to Improve Inventory Management Using AI
While traditional inventory management softwares can track and store data, it still requires massive human intervention to process the abundant data for effective inventory management. The more the amount of data generated, the harder it is to track every item in the inventory, let alone obtain any analytics of the same. Inventory management is getting increasingly complex, especially due to the global accessibility of data. This inventory management softwares were never built to handle such big networks.
The field of inventory management and logistics has recently been through a revolution owing to artificial intelligence and machine learning. Through machine learning and AI-based Inventory Management, companies can create smart data-driven manufacturing and distribution centers. The bigger the size of the distribution network, the better use can be made of trained AI. Let’s find out how.
Planning, Predictions, and Modelling
Overstocking and understocking are the biggest inventory management issues caused by traditional inventory management mechanisms owing to their failure to identify and adapt to the changes taking place in the demand of a particular product. To achieve such levels of accuracy in predictions, companies require extremely competent analysis, only made possible with AI-based Inventory Management. Today, artificial intelligence is providing insights that were previously impossible to achieve. AI can analyze as high as 50 elements simultaneously, and can be trained to factor in variables in real-time; something that is vital for optimizing planning, stocking, and scheduling deliveries. All in all, AI in supply chain management offers a much higher control over planning and operations.
Data Mining with AI in supply chain management software
AI-backed data mining is proving to be much easier and far more efficient than traditional information collection mechanisms. Artificial intelligence can take the data and turn it into actionable insights for businesses, making them better equipped to respond to a situation. AI-based algorithms are being used to track and record the interests, behavior, and preferences of consumers, to give businesses a plan for the future. For example, a cold drink manufacturing company uses AI in supply chain management to learn that the upcoming football match might lead to a hike in beverage sales. The company can very easily overstock their products for that particular region for that month, thus tapping on the minutest of opportunities.
Stock Management and Fulfillment
Inventory management heavily impacts customer satisfaction, customer fulfillment, and brand loyalty. Any shortages, delays in delivery, etc. can cause long-term, even permanent harm to the customer base as they are most likely to turn to competitors who were present at the right time with the right alternative. AI-based inventory management is capable of analyzing consumer behavior patterns and any number of other pre-set criteria to optimize stock planning, management, and fulfillment. Moreover, a trained AI even automates the process of stocking and suggests the best routes to improve the efficiency in delivery. It also heavily reduces prediction errors and mismanagement of stockings, thus saving huge sums of money.
AI-based Robotics
Companies like Amazon have already successfully implemented robotics in their day-to-day logistical tasks and the benefits are infinite. Robots offer a huge advantage over humans, especially in routine tasks. For example, a robot does not get tired of moving objects, locating wares, and scanning the items. They can work around the clock with practically no added costs for overtime or other expenses. This not only frees up a huge chunk of your logistics budget but also frees up internal employees for more important tasks that absolutely require human intervention.
AI in supply chain management, combined with the right human cognition, can become an extremely potent tool in automating processes, predicting demand and patterns, optimizing delivery routes, and much more.