C3.ai Inventory Optimization™ applies advanced AI/machine learning and optimization techniques to help manufacturers reduce inventory levels, while maintaining confidence that they will have stock when, and where, they need it.
Manufacturers often allow customers to configure hundreds of individual options, leading to products that could have thousands of permutations. Since the final configuration of a product is often not known until close to submission of the order, manufacturing companies need to have significant excess inventory on hand to be able to fulfill their orders on time. Over the years, manufacturing companies have deployed Material Requirements Planning (MRP) software solutions that support planning and automated inventory management. However, most MRP software solutions were not designed to optimize inventory levels by continuously learning from data.
C3.ai Inventory Optimization solves this problem by considering several real-world uncertainties including variability in demand, supplier delivery times, quality issues with parts delivered by suppliers, and production-line disruptions. The application dynamically and continuously optimizes reorder parameters and minimizes inventory holding and shipping costs for each part.
Reduce inventory holding costs and improve cash flow without compromising part availability. Optimize reorder parameters such as safety stock and safety time with necessary confidence levels.
Improve supplier management and negotiations through improved understanding of supplier performance. Simulate effects of changes in order parameters on supplier performance KPIs.
Increase visibility into critical uncertainties such as seasonality, uncertainty in arrivals, potential quality issues with suppliers, transportation bottlenecks, and production-line disruptions.
Enhance organizational efficiency through a common view across various departments (e.g., material management, supplier management, logistics management), leading to optimized inventory aligned with organizational goals.
Gain productivity of inventory analysts through automated recommendations based on new data and live integration with operational systems. Consistently apply recommendations to supplier orders.
Minimize total landed costs that include standard and expedited shipping costs, as a result of reduced inventory in the supply chain.
C3.ai Inventory Optimization aggregates data from different disparate source systems including production orders (actuals and planned), product configurations, bills of material, inventory movements (e.g., arrivals from suppliers, consumption in a production line, intra- and inter-facility shipments), historical settings of reorder parameters, lead time and shipping costs from suppliers, and part-level costs for each location where inventory is maintained.
C3.ai Inventory Optimization factors in several real-world uncertainties including variability in demand, supplier delivery times, quality issues with parts delivered by suppliers, and production line disruptions. The application uses machine learning to analyze variability, dynamically and continually optimize reorder parameters, and minimize inventory holding and shipping costs for each part.
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