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Analysis Study Research Paper | Information Technology | United States of America | Volume 13 Issue 9, September 2024 | Rating: 5.4 / 10
Leveraging Oracle ASCP and AI for Material Liability Management in Modern Supply Chains
Dipak Dilip Kulkarni
Abstract: Material liability for a customer arises from excess inventory resulting from mismatches between customer demand and material supply. This often occurs when companies order materials based on inaccurate demand forecasts or customer orders, leading to surplus inventory. Different business models influence how material liability is calculated: in Make-to-Stock (MTS), liability is linked to internal decisions or customer forecasts; in Make-to-Order (MTO), liability arises from excess material when a customer changes orders; and in discrete manufacturing, liability may involve multiple customers, complicating the allocation process. Liability is calculated by netting supply (e.g., purchase orders, inventory) against demand (e.g., sales orders, forecasts). Oracle Advanced Supply Chain Planning (ASCP) and Oracle E-business (EBS) can streamline this process by identifying excess materials. However, challenges arise in assigning liability when excess material is shared among multiple customers or product families. In cases of demand rescheduling or cancellations, material liability can be distributed based on demand volume or percentage allocations. AI can enhance this process by improving demand forecasting, automating netting calculations, and detecting anomalies in customer behavior. It can also support automated overrides, making liability adjustments more accurate. Frequent updates and manual overrides further ensure liability accuracy, especially in complex manufacturing environments. This journal explains liability concept and how could be derived by customizing Oracle EBS and ASCP application. This also highlights the assumption and corresponding limitation which could further enhance by plugging AI-capabilities.
Keywords: Liability, Material Liability, Supply Chain, Oracle EBS, Oracle ASCP
Edition: Volume 13 Issue 9, September 2024,
Pages: 658 - 661