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Faster, Smarter, Leaner: How Flipkart Optimized Its Supply Chain to Unlock Growth.

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Title: Faster, Smarter, Leaner: How Flipkart Optimized Its Supply Chain to Unlock Growth.
Authors: Agarwal, Shubham (AUTHOR), Agrawal, Prateek (AUTHOR), Allamsetty, Anurag (AUTHOR), Attavar, Adarsh (AUTHOR), B, Deekshith (AUTHOR), Bellala, Gowtham (AUTHOR), Bhatnagar, Shobhit (AUTHOR), Choudhari, Hardik (AUTHOR), Goel, Vikas (AUTHOR), Gupta, Praveen (AUTHOR), Kachroo, Ananth (AUTHOR), Kothadiya, Jay (AUTHOR), KM, Nagesh (AUTHOR), Kudupudi, Sai Anjani Kumar (AUTHOR), Kumar, Mayank (AUTHOR), KVM, Naidu (AUTHOR), Modi, Tanu (AUTHOR), Moorthy, Ramkumar (AUTHOR), Nair, Rakesh S. (AUTHOR), Panyam, Goutham Sai (AUTHOR)
Source: INFORMS Journal on Applied Analytics. Jan/Feb2026, Vol. 56 Issue 1, p42-57. 16p.
Subjects: Machine learning, Process optimization, Electronic commerce, Internet stores, Resource allocation, Capacity requirements planning, Inventory control, Flipkart Online Services Pvt. Ltd.
Geographic Terms: India
Abstract: The paper describes the work done by Flipkart teams since 2021 in building a central planning platform to help automate and optimize Flipkart's vast suite of retail operations. The platform transformed Flipkart's central planning and operations, and enabled it to grow sustainably and succeed in a dynamic and evolving market. It helped Flipkart achieve significant reductions in costs and higher delivery speeds through better inventory, capacity, and network flow planning. Beyond the impact on business metrics, it had a transformational impact on the organization, enabling higher productivity and agility across their planning, operations, and business partners.] The Flipkart Group, one of India's foremost digital commerce entities, serves more than 500 million registered users and offers a vast selection of more than 150 million products, connecting customers with 1.4 million sellers. To keep pace with rapid growth and the evolving ecosystem of e-commerce in India, Flipkart embarked on a transformational overhaul of its supply chain planning technology in 2021. This transformation led to the development of an advanced, fully integrated supply chain planning platform, built on machine learning and operations research techniques. The platform comprises two core layers: forecasting and optimization. The forecasting layer leverages a suite of statistical and machine learning techniques to produce multilevel demand forecasts. The optimization layer converts forecasts into actionable decisions across three key domains: inventory management, capacity planning, and network flow planning. These decisions collectively maximize delivery speed and reliability, minimizing operational costs. Flipkart has scaled this platform to automate and optimize end-to-end supply chain operations. Its impact has been profound: leading to a 10% increase in manpower utilization, a 50% reduction in unhealthy inventory, and a 50% increase in one-day deliveries. [ABSTRACT FROM AUTHOR]
Copyright of INFORMS Journal on Applied Analytics is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Faster, Smarter, Leaner: How Flipkart Optimized Its Supply Chain to Unlock Growth.
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  Data: <searchLink fieldCode="JN" term="%22INFORMS+Journal+on+Applied+Analytics%22">INFORMS Journal on Applied Analytics</searchLink>. Jan/Feb2026, Vol. 56 Issue 1, p42-57. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+commerce%22">Electronic commerce</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+stores%22">Internet stores</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Capacity+requirements+planning%22">Capacity requirements planning</searchLink><br /><searchLink fieldCode="DE" term="%22Inventory+control%22">Inventory control</searchLink><br /><searchLink fieldCode="DE" term="%22Flipkart+Online+Services+Pvt%2E+Ltd%2E%22">Flipkart Online Services Pvt. Ltd.</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink>
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  Data: The paper describes the work done by Flipkart teams since 2021 in building a central planning platform to help automate and optimize Flipkart's vast suite of retail operations. The platform transformed Flipkart's central planning and operations, and enabled it to grow sustainably and succeed in a dynamic and evolving market. It helped Flipkart achieve significant reductions in costs and higher delivery speeds through better inventory, capacity, and network flow planning. Beyond the impact on business metrics, it had a transformational impact on the organization, enabling higher productivity and agility across their planning, operations, and business partners.] The Flipkart Group, one of India's foremost digital commerce entities, serves more than 500 million registered users and offers a vast selection of more than 150 million products, connecting customers with 1.4 million sellers. To keep pace with rapid growth and the evolving ecosystem of e-commerce in India, Flipkart embarked on a transformational overhaul of its supply chain planning technology in 2021. This transformation led to the development of an advanced, fully integrated supply chain planning platform, built on machine learning and operations research techniques. The platform comprises two core layers: forecasting and optimization. The forecasting layer leverages a suite of statistical and machine learning techniques to produce multilevel demand forecasts. The optimization layer converts forecasts into actionable decisions across three key domains: inventory management, capacity planning, and network flow planning. These decisions collectively maximize delivery speed and reliability, minimizing operational costs. Flipkart has scaled this platform to automate and optimize end-to-end supply chain operations. Its impact has been profound: leading to a 10% increase in manpower utilization, a 50% reduction in unhealthy inventory, and a 50% increase in one-day deliveries. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of INFORMS Journal on Applied Analytics is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1287/inte.2025.0282
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        Text: English
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      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Process optimization
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      – SubjectFull: Electronic commerce
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      – SubjectFull: Internet stores
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      – SubjectFull: Resource allocation
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      – SubjectFull: Capacity requirements planning
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      – SubjectFull: Inventory control
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      – SubjectFull: Flipkart Online Services Pvt. Ltd.
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