Innovating Supply Chain Strategies: A Study of Strategic Flaws and Technological Gap in Supply Chain Management
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| Udgivet i: | IISE Annual Conference. Proceedings (2025), p. 1-7 |
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Institute of Industrial and Systems Engineers (IISE)
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| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3243713229 | ||
| 003 | UK-CbPIL | ||
| 024 | 7 | |a 10.21872/2025IISE_5157 |2 doi | |
| 035 | |a 3243713229 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 102209 |2 nlm | ||
| 100 | 1 | |a Mishra, Anubhav |u NYU Graduate Student | |
| 245 | 1 | |a Innovating Supply Chain Strategies: A Study of Strategic Flaws and Technological Gap in Supply Chain Management | |
| 260 | |b Institute of Industrial and Systems Engineers (IISE) |c 2025 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a Supply chain management has developed as a critical function in businesses worldwide, specifically with the increasing complexity of globalized markets. Behemoth companies like Walmart1,2 and others have created senior-level supply chain roles, underlining its strategic importance. Furthermore, the demand for supply chain professionals is projected to grow by 19% between 2023 and 20333, faster than the average for all professions. However, despite these advancements, supply chain methodologies remain scarce, leading to persistent challenges like demand-supply misalignment and inefficiencies in management. This research paper inspects two core hypotheses behind the persistent inefficacies in supply chain strategies: the inadequacy of current cost-minimization approaches and outdated supply chain technologies. To address these inefficiencies, we propose an integrated, adaptive supply chain model that leverages real-time data streams, AI-driven demand forecasting, and dynamic inventory management. Our methodology emphasizes speed and flexibility over static cost minimization by replacing legacy ERP-based planning with AI-powered predictive analytics. This includes real-time replenishment mechanisms, active volume monitoring, and predictive adjustments based on external signals such as seasonal trends and market events. The proposed strategy aims to significantly reduce inefficiencies, improve supply-demand alignment, and enable near-perfect order fulfillment rates, while still achieving long-term cost savings. By incorporating these modern technologies, businesses can build a more resilient, responsive, and future-ready supply chain framework. | |
| 610 | 4 | |a Procter & Gamble Co Walmart Inc Bureau of Labor Statistics | |
| 651 | 4 | |a United States--US | |
| 653 | |a Inventory management | ||
| 653 | |a Misalignment | ||
| 653 | |a Predictive analytics | ||
| 653 | |a Trends | ||
| 653 | |a Forecasting | ||
| 653 | |a Data transmission | ||
| 653 | |a Enterprise resource planning | ||
| 653 | |a Automation | ||
| 653 | |a Generative artificial intelligence | ||
| 653 | |a Suppliers | ||
| 653 | |a Order processing | ||
| 653 | |a Machine learning | ||
| 653 | |a Supply & demand | ||
| 653 | |a Technology adoption | ||
| 653 | |a Pandemics | ||
| 653 | |a Decision making | ||
| 653 | |a Cost reduction | ||
| 653 | |a Optimization | ||
| 653 | |a Flexibility | ||
| 653 | |a Supply chain management | ||
| 653 | |a Real time | ||
| 653 | |a Cost control | ||
| 653 | |a Inventory | ||
| 653 | |a Supply chains | ||
| 700 | 1 | |a Mazzone, Thomas |u Director of Industrial Engineering, NYU | |
| 773 | 0 | |t IISE Annual Conference. Proceedings |g (2025), p. 1-7 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243713229/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3243713229/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243713229/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |