Words Manish Kumar
NEW DELHI (India CSR): Artificial intelligence (AI) in supply chains can change the planning, manufacturing, management and optimization of supply chain activities. AI can enhance supply chain decision-making and operational efficiency by analysing enormous volumes of data, forecasting trends, and carrying out intricate operations in real time.
This technology has been more well-known recently as new developments like chatbots and generative AI have taken hold and demonstrated the systems’ potential benefits for supply chain management. In the meanwhile, the COVID-19 pandemic demonstrated the vulnerability of the global supply chain and the need for improved management systems.
One such practitioner, Simran Sethi, has made important contributions to supply chain optimization using Data Analytics & AI in her experience working in fashion tech and warehousing.
Through developing end-to-end data pipelines, she made possible the precise tracking of inventory, order fulfilment, and shipping status so that each phase of the supply chain would have real-time visibility, making it easier to map the complicated process. For a data startup, she used AI-based data governance solutions to streamline building construction schedules, procurement workflows, and resource allocation plans. By using real-time dashboards, stakeholders were able to see material requirements, construction status, and budget implications in real time, which improved planning and cost control.
Her work led to significant operational gains. At the fashion technology startup, automating inventory reporting cut report creation time by 20%freeing employees from manual data entry to make strategic decisions. In the warehousing industry, her AI-based procurement analysis reduced project overruns by catching potential delays early and allowing for timely resource redistribution.
Her demand forecasting models also maximized stock levels, decreasing warehousing overheads by 10–15% by avoiding excess inventory buildup. By standardizing cohort KPIs, Sethi provided consistency in measuring performance across product lines and regional markets, allowing finance, logistics, and product development teams to make decisions based on accurate, AI-driven analytics.
This expert also worked on application of real-time inventory management in the fashion tech industry. She created and implemented ETL pipelines to associate customer ordering behaviours with supplier lead times, thereby drastically decreasing the occurrence of backorders and boosting on-time shipment rates. She also integrated product analytics in both sectors, wherein she created real-time operational data solutions that turned insights into practical strategies for numerous teams. It made cross-department collaboration uniform and speed up decision-making.
Even as AI presents numerous benefits, Sethi faced and overcame various issues in deploying AI. Most companies have disparate data systems, where various departments store different datasets. To overcome this challenge, she developed centralized ETL infrastructures and standardized data schemas to provide AI models with access to clean, structured data. Moreover, rapidly evolving demand within the fashion segment and changing construction project requirements necessitated the creation of adaptive AI models that would keep pace with changing market trends.
By introducing dynamic inputs to forecast models, she enabled companies to predict shifts and react beforehand. Another main challenge was in unifying stakeholders with varying priorities, where procurement departments were interested in cost containment, marketing and product teams had concerns for agility and innovation. she met this challenge by adopting harmonized dashboards that show common performance measures, creating departmental alignment.
Reportedly Simran also highlighted the integration of sustainability metrics, such as carbon emissions and waste reduction data, alongside financial performance indicators, will drive more responsible supply chain decision-making
In the future, AI-based supply chains will increasingly be dependent on real-time visibility, enabling companies to forecast disruptions and act in anticipation. AI-based scenario planning and simulation will further help organizations simulate several strategies without experiencing actual costs or risks.
Simran Sethi’s contributions highlight the profound impact AI can have on optimizing supply chains. By implementing real-time analytics frameworks, predictive modelling, and AI-powered automation, she has helped businesses achieve measurable efficiency gains, cost reductions, and improved operational performance. As industries continue to embrace AI, those that prioritize data-driven decision-making and predictive analytics will be best positioned to navigate the evolving supply chain landscape successfully.
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Manish Kumar is a news editor at India CSR.
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