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Performance Management for High-Volume Transactions in Retail: A Data Governance Perspective

Updated on: 29 May,2025 03:57 PM IST  |  Mumbai
Buzzfeed | sumit.zarchobe@mid-day.com

One of the crucial contributions is his pioneering work in integrating SAP Master Data frameworks with advanced technologies like Machine Learning (ML).

Performance Management for High-Volume Transactions in Retail: A Data Governance Perspective

Arun Chinnannan Balsubramanian

Retail companies operate in increasingly complex environments, as large volumes of data concerning transactions like product information, financial data, and inventory details, must be integrated seamlessly in diverse platforms. More work, supply chain visibility, personalized customer experience, and predictive analytics are increasingly drawing on real-time data, making the apt management of data far more critical to success. As they scale their digital operations, retailers do encounter difficulties associated with pricing inconsistencies across omni-channel platforms, discrepancies in article master data, and problems maintaining proper product assortments. The issues must be solved in new and scalable ways, providing data consistency, refining operations, and enhancing business performance.


Arun Chinnannan Balsubramanian, an expert in ERP systems, data governance, and process engineering, has been at the forefront of addressing these complexities. With over two decades of experience across Telecom, High-Tech, Retail, Discrete Manufacturing, and Pharmaceuticals, his work merges technical ingenuity with strategic oversight to significantly improve operational efficiency. Arun’s approach to data governance directly tackles industry pain points through rigorous master data profiling, ensuring consistent pricing strategies, precise inventory management, and seamless product assortment management across channels.

One of the crucial contributions is his pioneering work in integrating SAP Master Data frameworks with advanced technologies like Machine Learning (ML). His projects, such as "Machine Learning-Driven Data Quality Management in SAP MDG," have introduced enhanced data accuracy, predictive analytics, and real-time monitoring, significantly improving the reliability of high-volume transactional data for retail enterprises.

Additionally, his white paper, "Lean and Green: Sustainable SAP Archiving for Modern Enterprises," outlines innovative frameworks that reduce performance bottlenecks, mitigate compliance risks, and lower storage costs. By systematically declassifying data, aligning archival practices across business units, and introducing automated lean processes, he has driven substantial operational efficiencies.

In retail serialization, projects like "Store Serialization Using SAP-IS Retail" have transformed legacy, non-serialized systems into robust serialized frameworks, improving inventory accuracy, reducing operational costs, and enhancing loss prevention strategies, thereby positively impacting profitability.

Recognizing the critical importance of cyber-security in increasingly interconnected supply chains, he has also been instrumental in implementing Cyber Supply Chain Risk Management (C-SCRM) strategies within SAP S/4HANA environments. The meticulous alignment of ERP functionalities with NIST cyber-security frameworks exemplifies his proactive approach to safeguarding retail operations from data breaches and operational disruptions.

With the innovative work in reverse logistics, including the integration of Intelligent Machine Vision systems with the SAP Business Technology Platform (BTP), he further transformed returns management. This approach significantly reduces manual inspections, accelerates decision-making for disposition processes, and improves value recovery from returned merchandise, reinforcing his forward-thinking approach.

One of the papers, "Repair Capitalization for Reverse Valuation in Supply Chain," earned multiple awards from Verizon Communications, delivering $42 million in financial benefits. This initiative underscores his ability to drive financial value through robust data governance and optimized supply chain processes.

Arun Chinnannan Balsubramanian’s extensive expertise in retail performance management, AI-driven analytics, cyber-security, and master data governance has made him a transformative force in modernizing high-volume transactional environments. His unique blend of technical acumen and strategic insight continues to set new benchmarks for innovation and operational excellence in the retail sector.

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