Multi-period Newsvendor Model

TL;DR

This paper extends the classic newsvendor model into a multi-period setting for manufacturing, optimizing production batch size to enhance profitability and adaptability, outperforming traditional models and safety stock approaches.

Contribution

It introduces a multi-period newsvendor model tailored for manufacturing firms, incorporating costs and demand variability, with demonstrated superior profitability and robustness.

Findings

Higher profitability compared to traditional models

Fewer stock-outs and lower inventory levels

Robust to demand distribution mismatches

Abstract

The newsvendor model is a well-known stochastic model for inventory management; however, it was originally developed for a single-period context and focuses on trading companies. This paper proposes an extension of the newsvendor model into a mutli-period setting, aiming to develop a decision-making tool for manufacturing firms to determine the optimal production batch size. The objective function is to maximize operating profit in accordance with generally accepted accounting principles. The model can also incorporate overhead costs, such as warehousing, shrinkage, cost of capital, and lead time between the production decision and output. Monte Carlo simulations demonstrate that the proposed model results in higher profitability compared to other newsvendor models used in our analysis, as well as the safety stock buffer approach. The key feature explaining its outperformance is better adaptability of the production batch size, that leads to fewer stock-outs relative to other newsvendor models and lower inventory levels compared to the safety stock buffer approach. The robustness analysis shows that the proposed model is quite tolerant of mismatches between the "model" and the "true" demand distributions. Finally, we provide some recommendations on selecting the appropriate "model" distribution for different SKUs.