Leveraging Data Analytics for Effective Working Capital Management: Evidence from the Indian Steel Industry

Dr. Shiv Ji Verma , Khushbu Kumari

This study explores how data analytics can be leveraged to enhance working capital management (WCM) within the Indian steel industry. Using a secondary research methodology, it examines financial reports, academic studies, and industry analyses to understand the impact of analytics-driven practices on liquidity, efficiency, and profitability. The findings reveal that firms integrating analytics tools into their financial systems experience reduced cash conversion cycles, optimized inventory control, and improved receivable management. Predictive and prescriptive analytics enable managers to make data-informed decisions, ensuring better cash flow forecasting and risk mitigation. While challenges such as data quality and skill gaps persist, the overall evidence highlights that analytics adoption significantly improves financial agility and competitiveness. The study contributes to the growing discourse on digital transformation and provides strategic insights for industrial firms aiming to achieve financial sustainability through data-driven decision-making.

Published Paper   E-Certificate

"Leveraging Data Analytics for Effective Working Capital Management: Evidence from the Indian Steel Industry", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.11, Issue 1, page no.b565-b577, January-2026, Available :https://ijsdr.org/papers/IJSDR2601171.pdf

Volume 11 Issue 1, January-2026

Pages : b565-b577

Paper Reg. ID: IJSDR_307062

Published Paper Id: IJSDR2601171

Downloads: 000226

Research Area: Commerce All

Country: prayagraj, Uttar Pradesh, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2601171

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2601171

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition