A Data-Driven Approach to Improve Artisans’ Productivity in Distributed Supply Chains
研究发现，在分布式供应链中，频繁且可预测的主管访问能显著提升工匠生产力；基于此开发的路径调度框架在实地试验中使织布速度提高16.7%，为农村女性织工增收提供了低成本方案。
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.