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Tech Data adds its expertise to sustainable fashion project

Tech Data is joining IBM, the UK Fashion & Textile Association (UKFT), the Future Fashion Factory and various retailers in the development of a technology platform designed to increase transparency within the fashion and textile supply chain. 

The nine-month Sustainable Supply Chain Optimisation project has been
set up to address a fundamental lack of transparency and visibility across the fashion supply-chain that makes it difficult for organisations to implement more sustainable practices and for consumers to shop more sustainably. 

The project aims to show how emerging technologies like blockchain and AI running on the IBM Cloud can overcome data silos and create a shared system of data that different parties can trust and act upon. 

This, it is hoped, will enable interested parties to gain a much better understanding of where and how each garment’s fabric was processed and finished, by whom and in what conditions, while also helping to reduce waste, for example through better monitoring of production processes and flows. 

The Sustainable Supply Chain Optimisation project has been awarded £1.4 million in funding by Innovate UK, part of UK Research and Innovation, on behalf of the Industrial Strategy Challenge Fund (ISCF) Manufacturing Made Smarter Challenge. 

Neil Cornish, Business Manager of Tech Data’s Ecosystems Programme UK, said: “We are delighted to offer our experience in supply chain management and technology platforms, our expertise in new technologies such as IoT, artificial intelligence and data analytics, and our deep relationships with retail ecosystem partners to this exciting project. Our team is looking forward to working with the consortium to develop and deliver a sustainable, transparent and efficient solution for the UK fashion and textiles industry.” 

Other parties involved in the project include retailers Next, H&M (COS brand), N Brown and New Look and yarn manufacturer Laxtons. 

https://uk.techdata.com/ 

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TechnologyReseller: 2021