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March 1, 2022
Be specific and always communicate at an SKU level. Communicating at an aggregate level leads to greenwashing.
Always explain how savings have been achieved over time to illustrate your improvement from an initial starting point.
Always link your results to an explanation about the methodology used.
Be prepared to present all inventory data and share a breakdown of your sources, including how much data is derived from primary vs secondary sources.
Diversify your secondary data sources, opting for a multi-source approach to ensure high quality and accurate results. Avoid single source secondary data.
Accompany impact figures with traceability of at least tier 1 & 2 of your supply chain.
Don’t forget that tier 3 of your supply chain probably contains multiple suppliers, especially if you’re using blended fibres.
Don’t communicate your savings without also mentioning your impact. It’s important for consumers to understand that each product they buy has an impact.
Don’t benchmark apparel items that are of different weights and or different fiber compositions.
For detailed explanations follow the link:
LCA
Environmental impact
Greenhouse gas
Secondary data
Primary data
Multiple source approach
Made2Flow was founded in 2019 by a team of fashion supply chain experts, environmental specialists & tech wizards to facilitate impact measurement & accelerate impact reduction across the supply chain in the fashion industry.
Made2Flow’s technology automates the data gathering & impact calculation process. Based on a proprietary machine learning algorithm it has developed a multiple source approach to increase data accuracy and data validation.
Related
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Made2Flow was founded in 2019 by a team of fashion supply chain experts, environmental specialists & tech wizards to facilitate impact measurement & accelerate impact reduction across the supply chain in the fashion industry.
Made2Flow’s technology automates the data gathering & impact calculation process. Based on a proprietary machine learning algorithm it has developed a multiple source approach to increase data accuracy and data validation.
