Data-Driven Warehouse Layout Optimization using Demand Analytics and Lean Principles: A Case Study of an Ayurvedic Distribution Centre

Abstract This study examines warehouse layout optimization in an Ayurvedic distribution centre through a data-driven and lean-oriented approach. In modern supply chain operations, warehousing plays a critical role in determining operational efficiency, order fulfilment speed, and inventory movement performance. The study focuses specifically on the issue of inefficient warehouse layout planning caused by unstructured SKU placement and the absence of demand-based zoning practices. The research identifies that the existing warehouse configuration evolved progressively without systematic analysis of SKU movement intensity or throughput contribution. This resulted in excessive travel distance during picking operations, congestion in active storage zones, uneven workflow distribution, and inefficient space utilization. To address these operational inefficiencies, the study applies analytical techniques such as ABC analysis and SKU velocity classification to evaluate historical demand behaviour and inventory movement patterns. A structured warehouse zoning framework was developed by aligning high-frequency and high-movement SKUs closer to dispatch and picking zones, while low-velocity items were repositioned strategically to optimize space utilization. Lean principles were also incorporated to identify and minimize non-value-adding activities such as unnecessary motion, redundant handling, and inefficient material flow. The findings indicate that demand-driven slotting and velocity-based zoning can significantly improve warehouse operational efficiency without requiring physical expansion of the facility. The proposed layout framework contributes to reduced picker travel distance, improved accessibility of fast-moving items, better workload balancing, and enhanced overall warehouse flow. The study demonstrates how integrating data analytics with lean warehouse management principles can support practical and scalable optimization in medium-scale distribution environments, particularly within the Ayurvedic supply chain sector. The research provides both academic and managerial insights into warehouse optimization practices and offers a practical framework that can be adapted by similar distribution-based organizations seeking operational improvement through structured inventory positioning and layout redesign.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-18
DOI
https://doi.org/10.5281/zenodo.20271686
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
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article

Data-Driven Warehouse Layout Optimization using Demand Analytics and Lean Principles: A Case Study of an Ayurvedic Distribution Centre

Amity University
Zenodo (CERN European Organization for Nuclear Research)
Advanced Manufacturing and Logistics Optimization
article

Data-Driven Warehouse Layout Optimization using Demand Analytics and Lean Principles: A Case Study of an Ayurvedic Distribution Centre

Amity University
article en

Abstract

Abstract This study examines warehouse layout optimization in an Ayurvedic distribution centre through a data-driven and lean-oriented approach. In modern supply chain operations, warehousing plays a critical role in determining operational efficiency, order fulfilment speed, and inventory movement performance. The study focuses specifically on the issue of inefficient warehouse layout planning caused by unstructured SKU placement and the absence of demand-based zoning practices. The research identifies that the existing warehouse configuration evolved progressively without systematic analysis of SKU movement intensity or throughput contribution. This resulted in excessive travel distance during picking operations, congestion in active storage zones, uneven workflow distribution, and inefficient space utilization. To address these operational inefficiencies, the study applies analytical techniques such as ABC analysis and SKU velocity classification to evaluate historical demand behaviour and inventory movement patterns. A structured warehouse zoning framework was developed by aligning high-frequency and high-movement SKUs closer to dispatch and picking zones, while low-velocity items were repositioned strategically to optimize space utilization. Lean principles were also incorporated to identify and minimize non-value-adding activities such as unnecessary motion, redundant handling, and inefficient material flow. The findings indicate that demand-driven slotting and velocity-based zoning can significantly improve warehouse operational efficiency without requiring physical expansion of the facility. The proposed layout framework contributes to reduced picker travel distance, improved accessibility of fast-moving items, better workload balancing, and enhanced overall warehouse flow. The study demonstrates how integrating data analytics with lean warehouse management principles can support practical and scalable optimization in medium-scale distribution environments, particularly within the Ayurvedic supply chain sector. The research provides both academic and managerial insights into warehouse optimization practices and offers a practical framework that can be adapted by similar distribution-based organizations seeking operational improvement through structured inventory positioning and layout redesign.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Advanced Manufacturing and Logistics Optimization
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Data-Driven Warehouse Layout Optimization using Demand Analytics and Lean Principles: A Case Study of an Ayurvedic Distribution Centre — Amity University · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS