A Data-Driven Approach to Improve Artisans’ Productivity in Distributed Supply Chains

Smarter Supervision Lifts Rural Weavers’ Productivity Frequent, predictable supervisor visits can be a powerful lever for boosting artisan productivity in distributed supply chains, according to a study conducted with Jaipur Rugs in India. Analyzing loom-level data, the authors show that reducing the average gap between visits by just one day raises weaving rates by 8.5%—with more substantial gains on complex rugs and when visits follow consistent schedules. Building on these insights, they develop a routing and scheduling framework that targets those looms most in need of support. In a 25-week field implementation covering about 6,000 visits across 200 looms, sites assigned to optimized routes saw a 16.7% increase in weaving speed relative to controls, highlighting a practical, low-cost pathway to higher earnings for rural women weavers. The research suggests that data-driven supervision in other supply chains with a similar structure (e.g., smallholder agriculture) could boost productivity and earnings, offering an operational lever for poverty alleviation at scale.

Authors

Institutions

Publication Details

Journal
Operations Research
Published
2025-10-27
DOI
https://doi.org/10.1287/opre.2024.1009
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Data-Driven Approach to Improve Artisans’ Productivity in Distributed Supply Chains

Divya Singhvi, Somya Singhvi, Xinyu Zhang
Operations Research
Supply Chain and Inventory Management
article

A Data-Driven Approach to Improve Artisans’ Productivity in Distributed Supply Chains

Divya Singhvi, Somya Singhvi, Xinyu Zhang
article en

Abstract

Smarter Supervision Lifts Rural Weavers’ Productivity Frequent, predictable supervisor visits can be a powerful lever for boosting artisan productivity in distributed supply chains, according to a study conducted with Jaipur Rugs in India. Analyzing loom-level data, the authors show that reducing the average gap between visits by just one day raises weaving rates by 8.5%—with more substantial gains on complex rugs and when visits follow consistent schedules. Building on these insights, they develop a routing and scheduling framework that targets those looms most in need of support. In a 25-week field implementation covering about 6,000 visits across 200 looms, sites assigned to optimized routes saw a 16.7% increase in weaving speed relative to controls, highlighting a practical, low-cost pathway to higher earnings for rural women weavers. The research suggests that data-driven supervision in other supply chains with a similar structure (e.g., smallholder agriculture) could boost productivity and earnings, offering an operational lever for poverty alleviation at scale.

Operations ResearchVol. 74(1)
University of Southern California (US), New York University (US)
Openalex Percentile: Top 50%
Supply Chain and Inventory Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.