Pros to Know: Tecsys' Kishore Balasubramanya Talks AI-Powered Demand Planning

As the director of product management and market strategy for Tecsys, Kishore Balasubramanya leads the development, execution and oversight of product vision for point-of-use supply chain solutions. His day-to-day responsibilities revolve around integrating advanced technologies to deliver solutions tailored to the unique demands of his users, such as those operating in resource-critical environments. This role combines deep supply chain domain knowledge with strategic market analysis to drive product innovation, optimize product-market fit, and ensure sustainable growth. Balasubramanya is focused on meticulous alignment of industry challenges and the enabling technologies that solve them. He focuses on AI-driven capabilities, such as predictive demand forecasting and IoT-enabled tools for real-time inventory tracking and supply chain optimization. His efforts emphasize addressing specific high-stakes end-user challenges, such as managing medical supply substitutions during disruptions and enhancing visibility across the supply chain. He continuously optimizes solutions by incorporating machine learning feedback loops and IoT system enhancements. He works closely with supply chain leaders and technology partners to uncover pain points like inventory shortages, overstocking, and logistical inefficiencies. From ideation to deployment and refinement, he is a keystone in bringing next-gen technology into supply chain realities. Through his efforts, he drives transformative outcomes, streamlines workflows, automates critical processes, and ensures adherence to complex regulations. 

Over the past 12 months, one of Balasubramanya's standout achievements was the development and implementation of AI-powered inventory optimization and demand planning. By incorporating machine learning algorithms to analyze historical data and predict demand fluctuations, these solutions enabled organizations to achieve a 20% reduction in stockouts, reduced inventory carrying costs by 15%, and provided predictive insights into supply chain risks. He also spearheaded the automation of supply chain workflows using RFID technologies, barcode scanning, and AI/ML-based predictive workflow recommendations, reducing manual touchpoints in inventory management and order fulfillment, resulting in a 30% reduction in order cycle times. Balasubramanya's also championed the integration of emerging technologies such as computer vision and electronic shelf labels (ESLs) to provide real-time insights into inventory levels, including lot, serial and expiration tracking, while enabling item substitution when necessary. This effort improved decision-making speed, reduced waste from expired or misplaced inventory, and enhanced compliance by enabling precise tracking of critical supplies. 

First on the agenda for the next 12 months is enhancing clinical adoption and supply chain automation in the healthcare supply chain space. Balasubramanya is building on the success of current products by focusing on minimizing manual touchpoints, streamlining workflows and improving accuracy in order fulfillment and inventory management. He’s particularly intent on advancing real-time inventory visibility across facilities, with a vision of reducing operational inefficiencies by 20-30% while seamlessly integrating these improvements into clinical workflows. He plans to expand AI and machine learning capabilities within inventory optimization solutions; is working to embed advanced algorithms that will sharpen forecasting accuracy and demand planning, giving organizations the tools to reduce stockouts by 25%, improve inventory turnover, and optimize supply chain costs; and driving a meaningful reduction in waste. He is also working on developing voice-enabled solutions, allowing hands-free interactions for supply chain operators and clinicians in fast-paced or sterile environments. 

We talked exclusively with Balasubramanya about AI-powered inventory optimization and demand planning and what supply chain automation looks like in the healthcare supply chain space.

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