Made-to-Order vs. Made-for-Stock: Which Requires More Investment?

Pentland innovating with AI

As mentioned by our guest lecturer Katie Greenyer, brands have shifted from a made-for-stock model to a made-to-order approach after integrating AI, significantly reducing costs. Traditionally, made-for-stock required heavy upfront investment in manufacturing, storage, and logistics, with the risk of excess inventory if products didn’t sell. In contrast, made-to-order minimizes inventory costs by producing only after an order is placed. However, it can come with higher per-unit production costs since it lacks the economies of scale that bulk manufacturing provides. Additionally, brands may need to invest in AI, supply chain management, and real-time tracking systems to ensure efficiency and maintain customer trust despite longer lead times.

While made-to-order may require initial investment in technology, it ultimately reduces financial risk by preventing overproduction and unsold stock. AI-driven demand forecasting and automated production processes can further enhance cost-effectiveness, making this model a sustainable and financially viable alternative. As businesses continue to explore smarter manufacturing methods, balancing customer expectations with production efficiency will be key to successfully implementing a made-to-order approach.