Today's supply chains move at a ferocious pace fueled by multiple data streams from both internal and external enterprise systems, social networks, syndicated streams, Internet of Things (IoT) and more.
Advances in machine learning help transform this data to better predict customer needs, identify trends and deliver a more synchronized supply chain from product concept to customer availability.
Inventory Optimization (IO) can have a huge financial impact by freeing up working capital while boosting service and minimizing inventory.
Harnessing the insights of multiple data streams, IO determines where and how much stock to hold to meet a designated service level while complying with specific inventory policies. Through sophisticated machine learning algorithms, IO makes stocking recommendations to satisfy these needs.