Towards a mass customization in the fashion industry: An evolutionary decision aid model for apparel product platform design and optimization

Abstract To meet the diverse needs of customers with a competitive offering, many companies are utilizing product families and platform-based product development to increase variety, shorten lead times and reduce costs. However, current research in this area does not sufficiently examine broader enterprise considerations, such as production and inventory management complexity and costs, or expected sales. Furthermore, very few existing platform design methods integrate fitting and ergonomic considerations in their formulation. This study proposes a two-stage platform-based design process to support apparel brands to implement mass customization (MC) strategies. This work has been conducted in collaboration with Yamamay, an Italian underwear and lingerie brand. In the first stage, the characteristics of a scale-based platform (i.e. the number of product variants) are determined based on (i) the results of the anthropometric analysis of a large Italian female population sample, (ii) business considerations discussed together with brand managers and experts, (iii) and benchmarking data. In the second stage, a novel and ad-hoc developed evolutionary-based decision aid model stretches and shrinks the resulting classes looking for the optimal trade-off based on anthropometric data between the demand of garments that fit well and the percentage of the population that is satisfied with the proposed product family. The approach proposed here has been proved effective not only in theory but also in practice through a pilot launch of a test product family. Integrating scale-based platform design of apparel with ergonomic, production, inventory, and sales considerations makes this study unique and paves the way for the implementation of customization-as-a-service business model and for the transformation of the fashion industry into a technology- and knowledge-intensive industry.