https://csdb.sciforce.org/CSDB <p>Advancing Knowledge in International Journal of Computer Science and Data Engineering: About Computer Science and Database Applications (CSDA) by Sciforce Publications</p> <p>Welcome to International Journal of Computer Science and Data Engineering (CSDA), an esteemed publication by Sciforce Publications. CSDA serves as a dynamic platform for disseminating cutting-edge research, innovative technologies, and transformative ideas in the fields of computer science and database applications. In this "About Us" section, we will provide an overview of CSDA, its mission, and its dedication to fostering advancements in computer science and database technologies.<strong> </strong></p> en-US [email protected] (Dr. Suryakiran Navath, Ph. D.,) [email protected] (Technical) Wed, 21 Jan 2026 05:12:49 +0000 OJS 3.2.1.4 http://blogs.law.harvard.edu/tech/rss 60 https://csdb.sciforce.org/CSDB/article/view/271 <p>The medical technology (Med-Tech) industry operates within a highly complex supply chain environment shaped by strict regulatory requirements, high product variability, global manufacturing networks, and the critical need for uninterrupted product availability. Through our direct involvement with the case organization, we observed that these challenges resulted in fragmented planning processes and limited end-to-end visibility.</p> <p>This paper presents a large-scale end-to-end (E2E) supply chain transformation implemented at a global Med-Tech organization. We led the initiative with the primary objective of replacing disconnected planning and execution systems with a unified, ERP-centric planning platform. This transformation enabled improved transparency, increased planning reliability, and more proactive decision-making across the supply chain.</p> <p>Following implementation, we measured significant performance improvements, including higher forecast accuracy, improved inventory utilization, stronger customer service levels, and increased cross-functional alignment. In addition, the organization established a scalable digital foundation to support future growth and increased operational complexity.</p> <p>By integrating advanced technologies such as artificial intelligence, machine learning, and cloud-based analytics with enterprise resource planning systems, we observed forecast accuracy improve from approximately 60% to as high as 97%, while effectively managing nearly $7 billion in inventory.</p> <p>Based on our first-hand implementation experience, this case study demonstrates how Med-Tech organizations can address supply chain complexity through a holistic transformation approach that aligns technology, data, processes, and organizational culture around a single, trusted source of truth.</p> <p>From our direct implementation experience, the most significant shift was the organization’s move from reactive expediting to capacity-aware, forward-looking decision-making.</p> <p>Keywords: ERP systems, supply chain transformation, medical technology, Med-Tech, demand forecasting, artificial intelligence, inventory optimization, digital transformation, Healthcare 4.0, organizational change management</p> Naidu Paila Copyright (c) 2026 Naidu Paila https://creativecommons.org/licenses/by-nc/4.0 https://csdb.sciforce.org/CSDB/article/view/271 Tue, 20 Jan 2026 00:00:00 +0000