An Application of Newsboy Problem in Supply Chain Optimisation of Online Fashion E-Commerce

TL;DR

This paper presents a supply chain optimization model for online fashion e-commerce that predicts SKU quantities using historic data to optimize fulfillment and utilization metrics, demonstrating improved performance over baseline methods.

Contribution

The paper introduces a simple, effective supply chain model tailored for online fashion retail, combining predictive analytics with optimization to enhance key operational metrics.

Findings

Model outperforms baseline regression solutions

Optimizes fulfillment and utilization indices

Easy to implement and deploy in real-world settings

Abstract

We describe a supply chain optimization model deployed in an online fashion e-commerce company in India called Myntra. Our model is simple, elegant and easy to put into service. The model utilizes historic data and predicts the quantity of Stock Keeping Units (SKUs) to hold so that the metrics "Fulfilment Index" and "Utilization Index" are optimized. We present the mathematics central to our model as well as compare the performance of our model with baseline regression based solutions.