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New Innovation and Idea | Transport Studies | United States of America | Volume 13 Issue 6, June 2024 | Popularity: 5 / 10

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From Chaos to Control: How AI and SAP TM Are Making Supply Chains Immune to Disruptions in Unpredictable Times

Sudhir Makkar

Abstract: Today's supply chain is a complex, interwoven system that can be disrupted by a range of unanticipated events, including war, civil upheaval, natural disasters, and technology setbacks. Resilience and continuity in supply chain activities depend on how well these disturbances are managed. To proactively manage supply chain interruptions, this study investigates the integration of Artificial Intelligence (AI) into SAP Transportation Management (SAP TM). SAP TM may improve supply chain visibility, responsiveness, and decision-making processes by utilizing AI's predictive analytics, machine learning algorithms, and real-time data processing capabilities. This paper explores novel aspects of integrating AI in the Supply chain with an emphasis on SAP TM and evaluates the body of research on supply chain management and AI by industry practitioners. Promising advantages of AI-driven systems include better prediction accuracy, shorter lead times, and better on-time delivery performance. For instance, AI can help reduce supply chain costs by up to 20% and improve inventory turnover rates by 25%, according to McKinsey & Company [1]. Globally supply chains have recently encountered unseen challenges. Natural disasters, wars, terrorism, sociopolitical upheavals, pandemics, and man-made catastrophes have all brought the globe to its knees, highlighting the necessity for supply chains to be proactive and resilient. AI and sophisticated data modeling approaches are now essential tools for lessening the effects of disruptive and disastrous occurrences in the supply chain. To increase insights and prediction capabilities for a variety of scenarios, such as the collapse of the Baltimore Bridge, the conflict in the Middle East, the crisis in Ukraine, etc., this abstract investigates how we might take advantage of the developing capacity of AI to create models that mix real and synthetic data.

Keywords: Transportation Management, AI, SAP S/4 HANA, Supply Chain Resilience

Edition: Volume 13 Issue 6, June 2024

Pages: 1769 - 1773

DOI: https://www.doi.org/10.21275/SR24625065642

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