# Demand forecasting techniques for build-to-order lean manufacturing supply chains

## TL;DR

This paper introduces a new data set and a novel data transformation technique for demand forecasting in build-to-order supply chains, demonstrating competitive results with existing methods.

## Contribution

It provides a unique BTO-specific data set and a new data transformation approach, addressing a gap in demand forecasting research for BTO supply chains.

## Key findings

- The proposed method performs comparably to state-of-the-art techniques.
- The data transformation technique is easy to implement and interpret.
- Thirteen forecasting methods were evaluated with positive results.

## Abstract

Build-to-order (BTO) supply chains have become common-place in industries such as electronics, automotive and fashion. They enable building products based on individual requirements with a short lead time and minimum inventory and production costs. Due to their nature, they differ significantly from traditional supply chains. However, there have not been studies dedicated to demand forecasting methods for this type of setting. This work makes two contributions. First, it presents a new and unique data set from a manufacturer in the BTO sector. Second, it proposes a novel data transformation technique for demand forecasting of BTO products. Results from thirteen forecasting methods show that the approach compares well to the state-of-the-art while being easy to implement and to explain to decision-makers.