Magazine Supply Optimization: a Case-study

TL;DR

This paper presents AthenIA, an industrialized magazine supply optimization system that uses a novel quantile regression method and a four-step pipeline to improve supply planning for over 20,000 retail points in France.

Contribution

The paper introduces a new group conformalized quantile regression technique integrated into a modular supply planning pipeline for magazine retail.

Findings

AthenIA effectively balances out-of-stock and over-supply costs.

The solution improves supply efficiency for over 20,000 points of sale.

It addresses challenges like irregular sales and fixed inventory assumptions.

Abstract

Supply optimization is a complex and challenging task in the magazine retail industry because of the fixed inventory assumption, irregular sales patterns, and varying product and point-of-sale characteristics. We introduce AthenIA, an industrialized magazine supply optimization solution that plans the supply for over 20,000 points of sale in France. We modularize the supply planning process into a four-step pipeline: demand sensing, optimization, business rules, and operating. The core of the solution is a novel group conformalized quantile regression method that integrates domain expert insights, coupled with a supply optimization technique that balances the costs of out-of-stock against the costs of over-supply. AthenIA has proven to be a valuable tool for magazine publishers, particularly in the context of evolving economic and ecological challenges.