Research Highlights

Unraveling the Best Methods of Increased Productivity in Handmade Rugs

 Divya Singhvi Headshot

Overview: In “A Data-driven Approach to Improve Artisans' Productivity in Distributed Supply Chains,” NYU Stern Professor Divya Singhvi, PhD student Xinyu Zhang, and Somya Singhvi (USC Marshall) research ways to help artisans who make handmade rugs in India become more productive.

Why study this now: Artisanal supply chains, crucial to the global rural economy and a significant source of employment for women in the developing world, face issues of low productivity and high poverty levels. Furthermore, determining effective and realistic solutions to low productivity is difficult because of the nature of this fragmented supply chain – particularly because artisanal items like handmade rugs are often made in individual households.

What the authors found: Working with one of the largest hand-loom rug exporters in India and through conducting field visits and empirical analysis, the researchers identified:

  • A one-day decrease in the time between supervisor visits to the artisans can lead to a decrease in weaving time of 2.8%-14.1%, which can subsequently result in a 15%-17% increase in monthly income for the weavers due to increased weaving efficiency.
  • Visits to weavers with difficult-to-weave rugs and visits that are consistently scheduled are the most effective in improving artisan productivity.
  • Based on their insights, the researchers developed a “predict-then-optimize” framework, which can be used to plan and schedule visits in the most efficient way while considering a variety of constraints.

Key insight: The research shows that by having supervisors visit regularly and planning those visits more efficiently, the people making handmade rugs can earn more money and be more successful. They add that “the methods introduced in this paper can provide useful insights and tools for other researchers and practitioners to optimize supervision in other distributed supply chains in resource-constrained settings.”