ImpaktID leverages on over 50,000 data points to derive the most accurate fashion footprint analysis.

Our purpose to develop 

Impakt ID

In the midst of incredible greenwashing, we believe transparency and tangible impact are crucial to building consumer trust and enforcing a conscious enduring change in the way we produce, consumer and dispose of fashion. 

Impakt ID marks a revolutionary step in the direction of equipping brands with a seamless technology that enables continuous measurement, communication and mitigation of the environmental footprint of textile production and waste. 

Our science-based tools are touching over 50 000 data points to provide an impartial and accurate evaluation down to a single product level, to allow brands and customers to take account and act to reduce their footprint.

Choosing the most robust methodology

To build the algorithm that generates an impartial, comprehensive and accurate evaluation down to a single product level, our team applied the methodology underpinning the Life Cycle Assessment (LCA) approach. 

Life cycle assessment  is an environmental management tool that considers the impact towards certain pre-determined environmental issues over the lifetime of a product. Our choice of methodology was led by the recognition of LCA as the most robust tool to date to provide the systems perspective required to accelerate the shift towards more sustainable consumption and production patterns (UNEP 2016). 

 
 

The Cradle-to-Grave Framework

The scope of our LCA study is a cradle-to-grave (as opposed to cradle-to-gate which is confined to the manufacturing phase) to account for all the stages of a product lifetime, including raw materials extraction, manufacturing, transportation and distribution, use and disposal.

 

Due to the deficiency of rigorous, peer-reviewed scientific research on the environmental impact of user behaviour and consumption patterns, we have excluded the use phase from the assessment for the time being. We are aware of the significant contribution the use stage might have to certain environmental parameters (e.g. climate change) and will be working towards factoring this impact into a future version of the tool. 

use

CRADLE-TO-GRAVE

end of life 

raw material production

raw material

fiber preparation

GHG emissions

yarn preparation

energy

fabric preparation

water pollution

dying and finishing

water 

apparel manufacturing 

waste

CRADLE-TO-GATE

distribution

INPUT

PROCESS

OUTPUT

 

Leveraging on the largest dataset of verified and consistent data

The algorithm, set on primary and secondary peer-reviewed research, touches on 50,000+ data points, where we continuously enrich and update the database based on new research and findings. 

 

The secondary data that the algorithm utilises leverages on representative data derived from over 1,500 scientific journal articles and life cycle inventory (LCI) databases such as Ecoinvent and GaBi Professional, Idemat, and the Sustainable Apparel Coalition’s Higg Material Sustainability Index (Higg MSI) database.

 

All data sources that our algorithm relies on are based on an extensive structured analysis with representative samples and methodology. Our data analysis further takes into consideration and accounts for the differences in framework scope of the different researches and has mitigated the margin of error in results variation driven by the scope of the framework. That is, if one research has based their findings on the Cradle-to-Gate framework and another on the Cradle-to-Grave framework, our analytical framework would not treat the research findings as the final output data to include in our calculation algorithm, but would extrapolate and standardise the data to account for the methodological differences. Authenticity, time limit and geographical coverage of the secondary data sources are all aspects that were further carefully examined before using the data.

It is worth to mention that we found LCA studies with similar boundaries and geographic focus which reveal differing values for the environmental impact categories studied.  In such instances, and on the condition that the deviation is not significant, we have selected the most thorough and conservative estimates. In the cases of significant variance, we have carried out a statistical analysis to accurately interpret the data and understand the key factor behind such deviation.

 

Current assessment limitations

The tool is built to focus on the environmental impacts of textile production and end-of-life management and currently does not consider social and economic implications. The algorithm leverages solely on primary and secondary peer-reviewed verified data sources and would only consider enriching our dataset with third-party private data upon impartially verifying the methodology, research implementation and data interpretation are complete, exhaustive, unbiased and statistically representative.

 

What and how do we measure 

The impact assessment is the phase of the process aimed at understanding and evaluating the magnitude and significance of the potential environmental impacts throughout the life cycle of a product. Within the LCA framework there are two approaches to analysing the environmental impacts – a mid-point and an end-point approach. For the creation of our algorithm we resorted to the mid-point, also known as the problem-oriented approach, where the category impacts are translated into real phenomenon-based environmental themes such as climate change, water depletion, eco- and human toxicity. 

 

CO2 eq. footprint

Owing to the alarming consequences of climate change, the measurement of a product’s carbon footprint has gained a critical importance. The physical impacts (and resultant societal impacts) of the climate change are diverse, from sea level rise, extreme temperatures and disruptions to wildlife to implications for food and water security and patterns of disease.

A carbon footprint is the measurement of the amount of greenhouse gases (CO2, CH4, N2O, HFC, PFC and SF6) emitted as a result, either directly or indirectly, of human activity. This carbon footprint indicator can be applied to textile products in order to trace all relevant impacts throughout their lifecycle.

Each gas has its own global warming potential (GWP) based on its radioactive capacity compared to CO2.  GWP takes CO2 as the reference point of GHGs. That is why in our formula for GHG emissions the quantified result of carbon footprint is expressed in units of mass of carbon dioxide equivalents per 1 kg of fibre/fabric. 

The formula

kg CO2 eq./kg

To derive the basis for the formula for CO2 eq. emissions and/or savings at product level, we had looked at the impact generated at four “hot spots”:

 

  • Material impact

  • Wet processing and finishing

  • Manufacturing

  • Distribution

(

  M   *  MI       *    PW/PA    +         WP&FI   +  DI        *    PW    +   MOHI 

)

(

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (kg CO2 eq./kg)

PW = product weight (kg)

PA = product area (m2)

WP&FI = wet processing and finishing impact (kg CO2 eq./kg)

DI= distribution impact (kg CO2 eq./kg)

MOHI =manufacturing overhead impact (kg CO2 eq./type)

The formula is then tailored to different business models to arrive at the most accurate and actionable evaluation of the impact category. 

 
 

Pre-owned fashion product impact formula

To calculate the CO2 savings resulting from the purchase of a pre-owned item, we account for the sum of impact generated at the above four stages of the product lifecycle. The functional unit at the fabric production and shipping stages is a kg of fabric, whereas the manufacturing overhead is fixed on a product type basis. To achieve the highest possible level of precision and accuracy, the tool is built for calculating the CO2 eq savings of a garment made of more than one fabric. This means that if the piece is a blend of cotton and polyester in the ratio 90%-10%, the CO2 eq emissions are calculated separately and added to the total emissions in the exact same proportion.

The final CO2 eq emissions value is multiplied by a D Coefficient to demonstrate the savings resulting from the potential displacement of a new purchase as a result of a purchasing a pre-owned item.

(

  M   *  MI       *    PW/PA    +         WP&FI   +  DI        *    PW    +   MOHI   *  D

)

(

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (kg CO2 eq./kg)

PW = product weight (kg)

PA = product area (m2)

WP&FI = wet processing and finishing impact (kg CO2 eq./kg)

DI= distribution impact (kg CO2 eq./kg)

MOHI =manufacturing overhead impact (kg CO2 eq./type)

D coefficient (%) = the probability that purchasing a pre-owned piece would result in not buying a brand-new piece

 

Standard fashion product impact formula

We believe that knowing the impact of fashion is the main catalyst for action and change. That’s why we offer the option of calculating the CO2 eq emissions (net figures) for standard brands, considering the exact material the garment is made of and the impact at each stage of the product lifecycle. If the specific type of material is not available, such as Indian cotton, the tool would assume ‘conventional cotton’ impact. If a brand is using a special material and has known impact values for it, we will add it to the database and take this impact.

(

  M   *  MI       *    PW/PA    +         WP&FI   +  DI        *    PW    +   MOHI 

)

(

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (kg CO2 eq./kg)

PW = product weight (kg)

PA = product area (m2)

WP&FI = wet processing and finishing impact (kg CO2 eq./kg)

DI= distribution impact (kg CO2 eq./kg)

MOHI =manufacturing overhead impact (kg CO2 eq./type)

 

Sustainable

fashion product impact formula

To derive the CO2 eq emissions savings resulting from the production of a sustainable brand we compare:

 

  • The CO2 emissions for textiles that would be commonly used by mass fashion to create the product at hand (status quo emissions). 

 

To define the values for CO2 emissions, we looked towards peer-reviewed journals which have performed an extensive location-specific analysis with representative sample on the CO2 emissions by all the conventional textiles that status quo fashion would most commonly resort to for production.

 

  • The CO2 emissions for the textiles used to produce a sustainable garment. 
     

To define the values for CO2 emissions we conduct primary research on the textiles and practices the sustainable brands engage in, such as using superstar textiles or recycled/upcycled materials and innovative dyeing technologies.

-

(

  M   *  MI       *    PW/PA    +         WP&FI   +  DI        *    PW    +   MOHI 

)

(

)

(

  SQM   *  MI       *    PW/PA    +         SQWP&FI   +  SQDI        *    PW    +   SQMOHI 

)

(

)

SQM = status quo material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (kg CO2 eq./kg)

PW = product weight (kg)

PA = product area (m2)

SQWP&FI = status quo wet processing and finishing impact (kg CO2 eq./kg)

SQDI= status quo distribution impact (kg CO2 eq./kg)

SQMOHI =status quo manufacturing overhead impact (kg CO2 eq./type)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (kg CO2 eq./kg)

DI= distribution impact (kg CO2 eq./kg)

WP&FI = wet processing and finishing impact (kg CO2 eq./kg)

MOHI =manufacturing overhead impact (kg CO2 eq./type)

Rented fashion product impact formula

To calculate the CO2 savings resulting from renting an item as an alternative to purchasing a brand-new one, we factor in the RD coefficient to the basic formula. 

(

  M   *  MI       *    PW/PA    +         WP&FI   +  DI        *   PW   +  MOHI        *   RD

)

(

)

(

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (kg CO2 eq./kg)

PW = product weight (kg)

PA = product area (m2)

WP&FI = wet processing and finishing impact (kg CO2 eq./kg)

DI= distribution impact (kg CO2 eq./kg)

MOHI =manufacturing overhead impact (kg CO2 eq./type)

RD coefficient (%) = the probability that renting a piece would result in not buying a brand-new piece

 
 

H2O footprint

All textile production activities directly and indirectly rely on the availability of fresh water. Owing to the spike in population growth, essential resources like fresh water are becoming scarce. Consumption of water reduces the amount of water available for other uses, which, depending on the level of competition and the socio-economic context, can have consequences for the environment and people. According to the latest data (2019) from the World Resources Institute (WRI), 17 countries in total are experiencing ‘extremely high’ levels of baseline water stress and 44 countries are experiencing ‘high’ levels of water stress. 

This highlights the need to measure and account for the water footprint (WF), a concept that helps illustrate the consumption of water during a production process.  Water consumption is the volume of water that is evaporated, incorporated into a product or polluted to the point where the water is unusable. 

 

A comprehensive water footprint accounts for three elements:

 

 • Blue Water - refers to the volume of surface water and groundwater consumed during production processes. 

•  Green Water - refers to the volume of rainwater consumed. 

•  Grey Water - refers to the quantity of fresh water needed to mix desirable pollutants and maintain the required water quality as prescribed by agreed water quality standards.

 

In our formula for water footprint the quantified result of water consumption impact is expressed in:

The formula

m3 (eq.)/kg

To derive the basis for the formula for water footprint and/or savings at product level, we had looked at the impact generated at two “hot spots”:

 

  • Material Impact

  • Wet processing and finishing
     

The formula is then tailored to different business models to arrive at the most accurate and actionable evaluation of the impact category. 

(

  M   *  MI         *  PW   +   WP&FI   *   PW 

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (m3/kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (m3/kg)

The formula is then tailored to different business models to arrive at the most accurate and actionable evaluation of the impact category. 

 
 

Pre-owned fashion product impact formula

To arrive at the water savings, resulting from the purchase of a pre-owned item, we measure the water consumed at each “hot spot” and multiply the total impact by the D coefficient defined in the above section. As for CO2 emissions calculation, the algorithm takes into account product composition (exact materials and whether mono-material or blend), product weight and location of raw material growth and fabric manufacture. The impact of dyeing depends on the technology used where the usage of natural dyes and innovative technologies like GiDelave and ColorZen contribute to the reduction of water use and pollution.

)

(

  M   *  MI   *  PW   +   WP&FI   *   PW        *  D

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (m3/kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (m3/kg)

D coefficient (%) = the probability that purchasing a pre-owned piece would result in not buying a brand-new piece

 

Standard fashion product impact formula

To calculate the total water footprint of standard brands, we account for the water consumed (and polluted) during raw material extraction, fabric preparation, finishing and dyeing (also known as “wet processing”) and item manufacturing. 

The quantification of the impact allows brands to act on it by offsetting it and adopting strategies and technologies for reducing the impact in the longer term, with a focus on the areas that contribute the most to the overall value.

(

  M   *  MI         *  PW   +   WP&FI   *   PW 

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (m3/kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (m3/kg)

 

Sustainble fashion product impact formula

To quantify the water savings that can be achieved with a sustainable textile production, the algorithm compares:

  • The water footprint for textiles that would be commonly used by mass fashion to create the product at hand (status quo footprint); To define the volume of water consumed and polluted, we studied peer-reviewed journals and LCI databases which perform extensive location-specific analysis and even compare different irrigation and retting techniques.
     

  • The water footprint of sustainable textile production; To define the volume of water consumed and polluted we rely on secondary and where necessary we conduct primary research on the textiles and practices the sustainable brands engage in, such as using textiles that require less irrigation (e.g. bast fibers) or eco-dyed fabrics. 

-

(

  M   *  MI        *    PW/PA    +    WP&FI   *    PW    +   MOHI 

)

(

  SQM   *  MI       *    PW    +   SQWP&FI   *    PW    +   SQMOHI 

)

SQM= status quo material / fabric / fiber

MI = material impact

PW = product weight

SQWP&FI = status quo wet processing and finishing impact

M = material/fabric/fibre

WP&FI = wet processing and finishing impact

 

Rented fashion product impact formula

To calculate the water savings resulting from renting an item as an alternative to purchasing a brand-new one, we factor in the two coefficients described above: The R coefficient defined by type of garment and the RD coefficient (%). 

)

(

(

  M    *   MI           *    PW    +    WP&FI    *    PW       *   RD  

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (m3/kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (m3/kg)

RD coefficient = the probability (%) that renting a pre-owned piece would result in not buying a brand-new piece

 

Toxicity footprint

The use and emission of chemicals and the intrinsic toxic properties of some of these chemicals are an important topic in the textile industry. The quantitative evaluation of toxic impacts is an LCA approach termed toxic footprint. 

We have decided to add the calculation of toxic footprints as an output in our dynamic algorithm with the objective of steering the textile industry towards a more sustainable use of chemicals. The quantitative evaluation of toxic footprint assists in the comparison of the economic cost of production practices with their potential to improve environmental outcomes and thus guide product procurers, designers and other decision-makers in the textile value chain to make eco-efficient choices.

The USEtox model is the recommended method for quantification of the toxicity footprint by the ILCD handbook (European Commission, 2011) and the PEF (European Commission 2013). Among the model options, it offers the largest substance coverage with more than 1,250 substances and reflects more up to date knowledge and data than other approaches. It is used to measure emissions of chemical substances to air, water and soil and calculates the results in two impact categories: human toxicity and (freshwater) eco-toxicity. Moreover, it has the ability to consider spatial differences with the addition of location specific parameters.

In our formula for toxic footprint the quantified results are most often expressed in:

CTUh/kg (comparative toxic units, human toxicity)

 CTUe/kg (comparative toxic units, human toxicity)

or
 kg 1,4-DB eq (HTP) human toxicity potential

 kg 1,4-DB eq (FAETP) freshwater aquatic ecotoxicity potential 

The formula

To derive the basis for the formula for toxic footprint and/or savings at single-unit level, we had looked at the impact generated at the two most chemical-intensive processes:

 

  • Material impact

  • Dyeing

(

   M  *  MI       *  PW  +  WP&FI  *  PW       

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

The formula is then tailored to different business models to arrive at the most accurate and actionable evaluation of the impact category. 

 
 
 

Pre-owned 

fashion product impact formula

Identically to the CO2 eq emissions and water footprint calculation, and thanks to the modularity of the algorithm, the quantification can be tailored to four business models, where:

 

The overall toxicity footprint is multiplied by the D coefficient for pre-owned items to arrive at the savings resulting from purchasing pre-owned instead of new garments.

)

(

  M    *    MI        *    PW    +   WP&FI   *    PW         *   D     

)

(

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

D coefficient (%) = the probability that purchasing a pre-owned piece would result in not buying a brand-new piece

Standard 

fashion product impact formula

The overall toxicity impact is expressed in net figures for standard brands

(

   M  *  MI       *  PW  +  WP&FI  *  PW       

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

RD coefficient (%) = the probability that renting a pre-owned piece would result in not buying a brand-new piece

 
 

Sustainable 

fashion product impact formula

The overall toxicity footprint of sustainable items is compared to that of status quo brands, considering factors such as location, product weight and dyeing technologies, to arrive at the savings generated by sustainable brands

-

(

   M  *  MI       *    PW   +   WP&FI  *    PW       

)

(

   SQM  *  MI       *    PW   +   SQWP&FI  *    PW       

)

SQM = status quo material/fabric/fibre

MI = material impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

PW = product weight (kg)

SQWP&FI = wet processing and finishing impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

M = material/fabric/fibre (summing up to 100% of the composition)SQWP&FI = status quo wet processing and finishing impactWP&FI = wet processing and finishing impact

WP&FI = wet processing and finishing impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

Rented fashion product impact formula

The overall toxicity footprint is multiplied by the R coefficient and RD coefficients for rented items to arrive at the savings resulting from resorting to the rental service instead of purchasing a brand-new item.

(

  M    *    MI        *    PW    +   WP&FI   *    PW         *   RD     

)

(

)

M = material/fabric/fibre (summing up to 100% of the composition)

MI = material impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

PW = product weight (kg)

WP&FI = wet processing and finishing impact (CTUh; CTUe/kg or kg 1.4 DB eq./kg)

RD coefficient (%) = the probability that renting a pre-owned piece would result in not buying a brand-new piece

 

Waste Savings

After use, the large majority of textiles end up in landfill or incineration, the least preferred options after reuse and recycling.  This results in negative environmental, and subsequently, social impacts. Substances of concern that are contained in the textiles, such as any remaining dyes or chemicals that have been introduced during production or use, can leak out of the textiles as they degrade into the environment. If the waste is incinerated without controlling emissions, the combustion gases also have the potential to release substances of concern. These effects are exacerbated by the shift to shorter fashion cycles, leading to items being discarded by consumers very rapidly, despite being wearable. 

The formula

Sustainable brands, pre-owned fashion and collaborative consumption (rental) contribute to diverting textile waste from landfill or incineration. Increasing the average number of times clothes are worn is the most direct lever to capture value and design out waste and pollution in the textiles system. Our tool accounts for this by using the product weight as base for measuring the waste savings. 

 
 

Pre-owned fashion product impact formula

Reuse for primary purposes is considered among the best options for waste management, preventing all the environmental impacts related to landfilling, incineration or recycling. To calculate the waste savings resulting from the purchase of a pre-owned item instead of a brand-new one, the tool considers the product weight and the D coefficient.

  PW    *    D 

PW = product weight (kg)

D coefficient (%) = the probability that purchasing a pre-owned piece would result in not buying a brand-new piece

 

Sustainable fashion product impact formula

Sustainable brands contribute to the prevention or reduction of waste via practices that include, but are not limited to:
* Using pre-waste textiles, such as deadstock textiles (brand new textile leftovers that would have otherwise ended up in landfills)
* Using recycled or upcycled materials
* Using agricultural waste (e.g. orange peels, coffee grounds) or algae to produce fibres
* Adopting a focus on durability and timeless design
* Utilising pattern optimisation software to minimise the amount of textile waste; zero-waste design

  PW    *    SD 

PW = product weight (kg)

SD coefficient (%)  = reflects the percentage of the product weight that is associated to waste offset. 

 

Rented fashion product impact formula

The collaborative consumption models, such as rental services, offer another possibility of waste prevention via prolonging the active useful lifetime of garments, especially occasion wear. To calculate the waste savings resulting from renting an item instead of purchasing it, the tool considers the product weight and the RD coefficient:

  PW    *    RD 

PW = product weight (kg)

RD coefficient (%) = the probability that renting a pre-owned piece would result in not buying a brand-new piece

 

Circularity Qualitative Score

We are applying a zero-sum approach where we consider a product to either be circular or not. We differentiate between 4 types of circularity-enabling products:

 

100% recycled material 

The product supports a closed loop system by preventing non-healthy waste from entering the environment, regenerating materials and keeping them in use as long as possible.

 

100% upcycled material

The product supports a closed loop by turning waste into valuable, reusable material of enhanced quality. Materials are not processed but instead used as they come, with creativity as the main engine in the discipline. 

 

100% recyclable material 

The product is designed with recyclability in mind (either mechanical or chemical recycling process), following the principles of mono-material design, design for disassembly and transformability.

 

100% biodegradable material

 

We differentiate between 2 types of biodegradable products:

 

  1. Naturally compostable – a material symbiotically decomposes in soil, marine environments or conventional home composts. The material returns to the biosphere with zero negative environmental impact. This implies absence of toxic and/or carcinogenic components.
     

  2. Industrially biodegradable – the material is biodegradable under certain conditions (temperature, pressure). The biogas released during the degradation process can be used in alternative green energy industries.

In a circular textiles economy clothes, textiles, and fibres are kept at their highest value during use and re-enter the economy afterwards, never ending up as waste.

To ensure circularity, materials that go into a garment need to be safe and healthy to re-enter the economy in the closed-loop system. Design for material cyclability aims to eliminate the concept of waste and the need for virgin resources by enabling garments to be either recycled in a technical cycle or decomposed in a biological cycle.  A garment designed for material cyclability needs to be made in a mono-material design or in a multiple-cycle material combination which then needs to be designed for easy disassembly at end if use.

With this, we believe that assessing a piece's circularity on a proportion basis does not reflect the actual potential for this proportion to be circulated. In fact, if the piece is not 100% circular, it would not be circulated. This is  why we have opted for a 0-1 binary approach, where if the piece is <100% circular, then it is not circular. Assessing circularity is based on the product's ability to:


1. Circulate back to the value chain efficiently while generating less footprint than a virgin material


2. Circulate back to nature without impacting our nature's diversity, balance and health.

Building a better world through supporting the United Nations Sustainable Development Goals

Impakt ID empowers brands and customers to take account and act to reduce their footprint, supporting the achievement of the United Nations SDGs. By providing thorough, yet understandable, measurement of carbon (13), water (14) and waste (15) footprints at product level, the tool plays a critical role in the shift towards sustainable production and consumption (12). We strongly believe in the power of collectivism, pulled knowledge and combined resources. That is why we are continuously seeking collaborations and working closely with partnering organisations (17) to enable transparency and call for action throughout the industry (9).  

Areas of future development

This document aims at providing an extensive overview of the methodology and models underpinning our impact calculation algorithm. Drawing on first-hand knowledge of the textile industry and extensive science-based research on the environmental footprint at single product level, we made sure to arrive at the most accurate, comprehensive and technically advanced version of the assessment tool possible at the current moment. However, we have already identified areas of further development and charted a future version of the score methodology. 

Knowing that the environmental footprint at the use phase of the product lifecycle is not to be underestimated, we are looking into partnering with research institutions to perform a rigorous quantitative analysis of the environmental impact of user behaviour and consumption patterns. 

Currently, the LCIA (life cycle impact assessment) does not consider the social aspects across the supply chain, whereas improving the well-being of textile workers remains a paramount challenge. Being aware of the scale and severity of the issue, we are looking into incorporating social impact indicators, next to the environmental footprint evaluation. This has the potential to demonstrate the results of investing in fair working conditions and protection of human rights. 

Other areas of future study include but are not limited to the development of quantitative metric for product circularity, comprehensive assessment of the environmental footprint of all innovative dyeing techniques and investigation of the role that design and product durability can play in bringing more resource-efficient textile products. 

 
 
 
 

Want to learn more about the extensive methodology?

Write to us at hello@impaktid.com to learn more about the methodology. 

A data- and action-driven company on a mission to eliminate the footprint of fashion and preserve our environment.

ImpaktID 2020 © . Enabling an environment-neutral fashion industry.