Conversations with seasoned designers often reveal a depth of intuitive knowledge that's hard to quantify. Phrases like “I just know” in response to questions about fabric similarities, or near-perfect descriptions of fabric properties without consulting a fact sheet, are common. One anecdote from a product developer at a multi-billion dollar luxury Maison in Paris highlights how a senior colleague could instinctively, manually adjust tech packs with years of experience - no tech required. This innate understanding, honed over years of experience, is a potential goldmine of insight. Imagine the scalability and impact if this wealth of tacit knowledge could be translated into algorithms! To explore this potential, we delve into three specific use cases where digitising this deep, intuitive understanding could revolutionise fashion product development.
Fabric libraries are a crucial building block for achieving sustainability in fashion, acting as the definitive source for information on fabrics, a key component in a product's environmental footprint. In the quest for the ideal fabric library, product and sourcing teams across the fashion industry have envisioned libraries replete with comprehensive data — from fabric properties and supply chain details to subjective attributes like material feel or design intent. Yet, realising this vision has traditionally hinged on manual updates, a labour-intensive and costly process often deemed unfeasible. Many brands, including big players, struggle with creating complete, up-to-date libraries.
Product and sourcing teams across the fashion industry have envisioned fabric libraries replete with comprehensive data - yet, realising this vision has traditionally hinged on manual updates, a labour-intensive and costly process often deemed unfeasible.
What if we could automate this process? The potential to automate this process, leveraging algorithms to dynamically update and enrich fabric libraries, represents a significant leap forward. Envision a tool that rapidly builds and enriches fabric libraries by automatically allocating features like texture or design intent based on fabric properties. This automation could transform fabric libraries from static resources into dynamic, valuable assets, enhancing both sustainability efforts and design choices in fashion product development.
In the fast-paced world of fashion product development, integrating data-driven optimization needs to be seamless and automated from start to finish. Rather than relying on manual comparison tools, imagine the benefits of a recommendation engine that automatically proposes optimised design alternatives. Picture a product developer comparing fabric swatches: now, this process is augmented by algorithms capable of evaluating similarities between fabrics and instantly suggesting suitable alternatives. This approach not only offers substantial time savings but also unveils design options that might have been overlooked, opening new avenues for innovation, efficiency but also creativity in fashion design.
Rather than relying on manual comparison tools, imagine the benefits of a recommendation engine that automatically proposes optimised design alternatives.
Design for Durability is emerging as a crucial aspect of circular fashion, particularly with the upcoming EU regulations like Circular Economy Action Plan (CEAP) and Extended Product Responsibility (EPR). Seasoned designers inherently understand how fabric and construction choices affect a product's durability, but this knowledge is often unrecorded. Research organisations such as VITO and Flanders DC have worked on scientifically documenting these aspects, and published in 2023 a handy guide in PDF-format that sourcing and product teams can consult. But now, imagine integrating the hands-on knowledge of designers and the scientifically-backed methodologies into an algorithm that can instantly assess a design's durability score based on its materials and tech packs, and suggest enhancements. This approach would mark a substantial advancement in circular design, effectively transforming the rich, intuitive knowledge of experienced designers into practical, data-driven methodologies for advancing sustainable fashion.
Imagine integrating the hands-on knowledge of designers and the scientifically-backed methodologies into an algorithm that can instantly assess a design's durability score based on its materials and tech packs, and suggest enhancements.
The journey towards data-driven optimization in fashion product development is not just about embracing new technologies; it's about capturing and digitising the rich, yet often unspoken, wisdom of experienced designers. By transforming this deep, intuitive knowledge into sophisticated algorithms, we unlock a new realm of possibilities. Automated fabric library management, intelligent fabric similarity assessments, and durability evaluations represent just the beginning. This shift towards integrating seasoned insights with cutting-edge technology paves the way for a more efficient, sustainable, and innovative future in fashion design.
Design meets data: athena studio is the first solution that integrates financial and environmental performance early in fashion product development, enabling product teams to design towards their targets. Our platform visualizes the impact of each design and generates recommendations, offering an effective tool to integrate targets into teams’ day-to-day and to save time on manual, post-mortem analyses.
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