pef pilot key learnings & recommendations...

Key Learnings and

Recommendations Report

EU Product Environmental Footprint Pilot for non-‐leather shoes

29th July 2016

EU Footwear PEF Pilot Key Learnings and Recommendations Report July 29, 2016

TABLE OF CONTENTS

A. Executive Summary ........................................................................................................................................ 4 B. Industry Perspective ..................................................................................................................................... 10

1. The Specific Challenges Facing the Footwear Industry ............................................................................. 10 2. The Industry Perspective on Meaningful Environmental Footprinting ..................................................... 11

C. Technical Insights and Recommendations .................................................................................................... 13 1. Data Availability (Facilities and Materials) ................................................................................................ 13 2. Brands’ Internal Product and Material Systems and Product Composition Information .......................... 19 3. Methodology Challenges ........................................................................................................................... 25 4. Durability ................................................................................................................................................... 26 5. Scope of Benchmark Grades (A-‐E) for Footwear Categories Tested ......................................................... 27 6. Scalability challenges ................................................................................................................................. 30 7. Scalability, Resources and Costs ................................................................................................................ 32

D. Communications Vehicle and Testing ........................................................................................................... 34 1. Communications Test: initial qualitative insights from focus groups ........................................................ 35 2. Preliminary insights from brands in progress of market testing: .............................................................. 37

E. Harmonization Across European Initiatives .................................................................................................. 39


LIST OF FIGURES

Figure 1: Value Chain Web Complexity; Source: Outdoor Industry Association .................................... 11 Figure 2: Differentiation and lack of differentiation of scores for Brand A running shoes, sandals and boots ............................................................................................. 28 Figure 3: No change to scores for Brand C shoes using Detailed BOM tool when conventional materials were replaced with environmentally preferred materials (EPMs) ......................................... 29

LIST OF TABLES

Table 1: Comparison of factory environmental practices included in PEF methodology and SAC Higg Facilities Environmental Module (FEM) .................................................................................................. 15 Table 2: Synthetic leather assumptions (per kg by weight) .................................................................... 18 Table 3: Availability of material-‐level data in brands' databases ........................................................... 20 Table 4: Example of the limited data available for a Brand B shoe ........................................................ 21 Table 5: Example BOM for a Brand C shoe (Note: this table represents a snapshot of a BOM for a Brand C shoe; actual BOM for shoe includes approx. 5 times as many rows/materials) .................................. 22 Table 6: No variation in Brand C shoes using simple BOM. Simple BOM methodology results in worse scores compared to detailed BOM ......................................................................................................... 31 Table 7: Supplier default values versus actual measured values ............................................................ 31

LIST OF IMAGES

Image 1: Actual components in BRAND B shoe provided by Tier 1 supplier for the pilot (shoe name: Gary) ........................................................................................................................................................ 22

Image 2: Actual components in Brand C shoe provided by Tier 1 supplier for pilotError! Bookmark not defined.

Image 3: BRAND B shoes grouped into same category in PEF pilot ........................................................ 30

Image 4: PEF Performance label..............................................................................................................34


A. Executive Summary

Background:

The Sustainable Apparel Coalition (SAC) is an organization representing approximately 40% of the global apparel, footwear, and home textiles market. It is comprised of over 175 brands, retailers, manufacturers, academic experts, government, and non-‐governmental organizations who are working to lead the industry towards a more sustainable future. The SAC is positioning the Higg Index suite of tools to become the harmonized industry standard to measure global environmental and social impacts in apparel, footwear and home textiles value chains by 2020. Transparency between brands and suppliers, as well as consumers, is a strategic priority of the SAC to encourage the development of more sustainable products and processes. To that end, the SAC is well aligned with the goal of the European Commission in driving sustainable improvement of products.

In 2012 as part of the European Commission’s Single Market for Green Products initiative, the SAC was awarded the Product Environmental Footprint (PEF) Pilot for non-‐leather shoes. One of the main objectives for the pilot is to create a single environmental performance standard and test the effect of such a single standard on consumers’ understanding, awareness and behaviour. This initiative aims to test the effectiveness of calculating a product’s environmental impact from inception to end-‐of-‐life and sharing those findings with consumers through a communication vehicle. For the PEF pilot, the SAC convened a small group of leading brands and the Swiss Federal Office for the Environment (FOEN), to test and share environmental impacts across the lifecycle of footwear products.

The piloting brands, adidas, W.L. Gore, H&M, Inditex, Stella McCartney, NIKE Inc. and Vans (hereafter: the Brands) joined the Footwear Pilot to test and provide insights on whether a calculation approach based on Life Cycle Analysis (LCA) can be effective in real market situations and the reaction of consumers to this information through in-‐store labelling of individual products.

This report reflects only the position of the piloting brands and SAC. FOEN plays an advisory role in this pilot.

Objectives:

This report references our key findings and initial recommendations based on the main pilot objectives: • Test a standard for the industry to measure and communicate the environmental impact of

products to consumers to enable informed purchase decisions. • Test if communicating environmental information to consumers may influence the industry to

make improvements in the overall environmental performance of products.

Key Findings & Recommendations:

The findings included in this document are intended to reflect the collective experiences of the brands participating in the pilot over the last two and a half years. The market test has been completed by one of the six participating Brands. The remaining Brands are in various stages of testing or planning for market testing.

With respect to the first objective of creating and testing the standard for the industry to measure the environmental impact of products, our conclusion is that further work on the underlying tools and


methodologies is needed to support a standard that provides both meaningful differentiation of products and scalability to the industry. The work led by the SAC on the Higg suite of tools can address some of these needs.

Given the complexity of the footwear manufacturing processes and extended supply chain, there are challenges to capturing material-‐level life cycle data and factory-‐level impact data when applying the LCA tools currently available and recommended by the EU.

The EU PEF and SAC’s Higg suite of tools have a common vision: to evaluate product sustainability at a SKU1 level using LCA. We believe SAC’s suite of tools are complementary to EU goals. They focus on enabling an eco-‐system for efficient data exchange within the supply chain. By allowing for impact measurements at the materials, manufacturing facilities and brand level, the Higg Materials Sustainability Index (MSI), the Higg Facilities Environmental Module (FEM) and the Higg Brand module are essential enablers of an LCA assessment. They can generate the critical mass of consistent, comparable and scalable data needed to support accurate, verifiable and differentiating life cycle environmental information.

The second objective focused on testing if the communication of environmental product scores leads to the production of more sustainable products. Given most market tests are not complete as of July 29, it is difficult for the brands to draw final conclusions at this point. Preliminary insights are included in the market test section of this report.

Technical Findings:

Principle Challenges and Opportunities

The approach of the Technical Secretariat (TS) has been to develop a methodology that provides credible results and meaningful product differentiation without causing a barrier to participation for any organization – large or small.

As this summary will outline, the pilot highlights that improvements are needed to guarantee this objective in the future. Therefore we welcome further collaboration with the European Commission to align on a technical approach or method that is both scalable and differentiating.

1. Data Availability:

In order to create reliable, complete, comparable and clear information for consumers, brands need to gather detailed information across several levels of the supply chain. The industry’s complexity does not currently support this:

• Across the industry, there is a lack of consistent, comparable data across the supply chain for each brand’s materials, factory practices, and product attributes.

1 ‘SKU’ or Stock Keeping Unit is the identification numbers used to uniquely identify each product style and colour.


• On a smaller scale, there is a lack of access to existing data2. • Brands’ internal systems do not contain the necessary material and product composition

information required for the PEF methodology. • Some material or facility certification schemes (e.g., Bluesign, Better Cotton Initiative and

ISO14001) have not been evaluated to demonstrate whether or not they could be used to provide quantitative LCA impacts or qualitative environmental benefits where quantitative methodology gaps exist.

Recommendation: The result is that there is unlikely to be a high degree of data integrity. This will lead to an uneven playing field and loss of confidence and support for the program. To address these challenges, we recommend brands leverage the existing work and tools developed by the SAC including the Higg Index Facilities Environmental Module (FEM) and Material Sustainability Index (MSI) as well as other material databases like World Apparel & Footwear Life Cycle Assessment Database WALDB3 developed by a coalition of industry stakeholders in Switzerland. These tools and databases offer a consistent, standardized, and industry-‐aligned methodology to a) serve as a common language across the industry identifying and tracking material contents and specific manufacturing processes; b) measure the environmental performance of facilities (manufacturers) and c) provide qualitative measures to fill the methodology gaps identified in this pilot.

2. Methodology Maturity:

Life Cycle Analysis (LCA) methodologies do not yet have the capability to sufficiently model all relevant environmental impact areas with similar levels of accuracy. The pilot demonstrated that LCA methodology does not adequately address toxicity-‐related impacts or product durability for footwear.

Recommendation: As the scientific community continues to develop adequate approaches for evaluating the gaps addressed above we recommend using a qualitative approach to assess these impacts and create a holistic picture of environmental performance. As an example SAC has addressed this challenge at the materials level by its Materials Sustainability Index (MSI). While MSI is not a tool to measure a product’s environmental impacts, it uses indicators in the areas of toxicity (e.g. presence of chemical finishes), durability (type of product warranty), and end-‐of life (design considerations for care and disassembly) to address data gaps in material characterisation.

In addition to the LCA methodology challenges, in order to provide comparable results for PEF scores between products, more work is needed to determine the approach to either establish additional

2 Organizations like ÖKOTEX ® have access to large amounts of data along the supply chain. However, this data is not accessible for the industry at large scale. 3 World Apparel & Footwear Life Cycle Assessment Database (WALDB) has launched with the goal of providing environmental impact data for the fashion industry. More at: www.quantis-‐intl.com/files/2814/4654/3639/WALDB_FINAL_Nov_3_2015.pdf


footwear categories and/or redefine more specific benchmark classes or communicate an actual PEF normalized footprint value instead of a letter grade. Currently the benchmark classes (A-‐E) for the two footwear categories tested in the PEF Pilot are too wide and do not capture product-‐level differences.

3. Scalability Concerns:

The PEF methodology for scoring and assessments requires a great deal of data, expertise, time and resources. Due to the complex nature of the apparel and footwear industry supply chain, collecting the material, product and manufacturing data needed is highly resource intensive and sometimes impossible.

Many brands only have a business relationship with the final assembly factories and do not source raw materials directly. Materials can come from thousands of different suppliers around the world. Furthermore, brands have varying supply chain structures – some have more vertical relationships and others have much more diversity and spread amongst suppliers.

Brands found that it took between 5 and 30 hours to use the PEF methodology to assess and score each individual product. For a brand that produces 10,000 product styles a year this can be 50,000 to 300,000 hours of work each year. The range of hours reflects the wide variation of systems and available data that each brand has for tracking product, material, and supplier systems. The range also reflects the brands varying supply chain structures and relationships. For this Pilot we have used a tool that included data and assumptions and automated scoring. Without this, the investment of time and resources would have been even greater.

A critical value of this pilot is understanding the level of information and data required by brands for calculating an environmental score. This has allowed the participating brands to proactively engage their supply chain to understand the gaps. Because of the global and decentralized nature of the footwear and apparel industry, and the relative newness of capturing this level of information, it will require more than the handful of brands involved in this pilot to develop the infrastructure needed to make scoring possible on a broad scale.

Case Study: Small/Medium Enterprise:

The smallest (in size) brand involved in this pilot found that it would be nearly impossible to manage the level of data collection required by the PEF methodology for each product style each season. A majority of SMEs do not have systems to track each material in the shoe or the personnel to collect and manage the level of data required for the PEF methodology assessment and scoring. SMEs often only know a few of the main materials in the shoe and for those materials they may not know the full composition or weight. The smaller participating brands and its suppliers do not have in-‐house capabilities in Life Cycle Analysis (LCA) and found using the PEF methods challenging. The suppliers of the smallest brand in the pilot responded that it would not be feasible to implement this program at a larger scale and that it would be very challenging to provide the data required for the PEF. One of the pilot participants stated that “[our] suppliers are small and it is difficult for them to manage data requests like the ones needed for the PEF – they have to stop production work and manually weigh and collect the information. Getting the level of detail needed for the PEF Pilot took 4 to 5 people 8 days of work [from the Brand]. We have not been able to get an estimate of the time it took our supplier to support our request.”


Recommendation: Due to the significant investment that would be required from both brands and manufacturers across the supply chain, leveraging the existing work and tools developed by the SAC including the Higg Index Factory Environmental Module (FEM) and Material Sustainability Index (MSI) would produce a stronger return on investment. A key advantage to these kind of industry tools is the ability for the supply chain to share and collaborate on data gathered.

Preliminary Market Test Insights:

Although the findings are preliminary and based on small sample sizes, the findings between the SAC’s independent consultants, Salterbaxter, and the one Brand who has completed the market test, are providing valuable insights for the pilot as follows:

• Consumers understand A means best and E means lowest; however, there was confusion as to what factors led to the A and E

o It is easier for consumers to understand a one-‐to-‐one relationship (e.g. C score because of C level energy efficiency, for example when buying a fridge).

o However, the consumer loses the connection to the environmental score when there is one score derived from the amalgamation of many factors, as is the case with footwear and apparel.

• The ‘what’s in it for me’ factor was lacking for the consumer when choosing shoes based on performance, price and comfort over environmental scores.

Recommendations: SAC believes that transparent and credible communication of products’ environmental impacts is essential for scaling sustainability within supply chains. In order to be successful we must look to existing collaborative efforts that have leveraged more than a decade’s worth of work and millions of Euros in investment, to create scalable solutions for several of the challenges identified throughout the PEF pilot. Specifically the Technical Secretariat recommend the following:

• Investigate opportunities to leverage the Higg Index suite of tools. The SAC has made significant progress toward developing tools and processes that promote environmental transparency through the global supply chain. SAC invites collaboration in creating its tools and welcomes input from external initiatives and partners, like the European Commission.

• Develop a single solution that addresses transparency in a consistent manner for both the footwear and apparel product industries. The majority of the SAC’s member brands are working to address challenges across both footwear and apparel products. We endeavour to cooperate with the Product Environmental T-‐Shirt pilot and strive to align and (potentially) expand the methodology and outcomes of both pilots to be able to apply outcomes to the apparel industry.


While recommendations on communications will be included in the final report, pending completion of market tests, we believe that product labelling is just one of many options to address environmental performance transparency. The SAC aligns with the EU PEF vision of evaluating products at a SKU4-‐level using LCA, but the SAC also believes that, given the current technical challenges outlined in this report (i.e., lack of high-‐quality and comparable data between brands and suppliers, etc.) it is not advisable to communicate SKU-‐level scores to consumers. Other measures of sustainability performance, such as supply chain, material and brand-‐level performance, are on a quicker path to being standardized and consistently scored, and may provide an early platform for communication to consumers, to encourage sourcing from responsible brands, while the technicalities of SKU-‐level scoring are resolved.

SAC will be exploring this and several other communication vehicles through implementing its Higg Communication Roadmap to Transparency. This is a voluntary phased holistic approach to enable SAC members to be fully transparent about their facilities performance in 2018, their brand performance in 2019 and product environmental footprint performance in 2020. By 2020 SAC members will be able to be fully transparent about their Higg performance measurement.



B. Industry Perspective

1. The Specific Challenges Facing the Footwear Industry

The urgency and expanse of the sustainability issues facing the footwear industry requires collective attention on a global scale. No company alone can shift the existing industry paradigms. Addressing sustainability is important to the footwear industry as evidenced by the many efforts by individual companies and industry working groups, such as the SAC. Some of the key industry challenges and opportunities are summarized below, and described in greater detail throughout this report. Key industry challenges include:

Supply chain complexity:

The footwear value chain is complex and often not fully transparent for the companies involved. Most footwear companies only have a relationship with the final assembly factories (Tier 1, as shown in Figure 1). Brands often do not source raw materials directly, instead the factories generally do. Materials can come from thousands of different suppliers around the world (Tier 2, as shown in Figure 1). For example it is common for large brands to use more than 30,000 different materials – everything from exotic leathers to electronics and nearly every type of polymer. As a result, collecting data can be very complex and resource intensive. Furthermore, the structure of the supply chain is very different among brands. Some have more vertical relationships and others have much more diversity and spread amongst suppliers. A pictorial example of the complex value chain of Retailers, Brands, Agents, Factories, Material Suppliers, Raw Material Suppliers, and Chemical Companies is shown in figure 1. It should be noted that materials, manufacturing processes and the product’s lifetime often have the greatest environmental impact over the lifecycle of footwear.


Figure 1: Value Chain Web Complexity; Source: Outdoor Industry Association

Brands and retailers generally design product concepts, and the sourcing agents or factories generally develop the functional and actual product for retail. In some cases, the brands choose from their sourcing agents’ selection of designs. Because of this: • Brands and retailers often have limited information on the exact contents of their shoes • Brands and retailers often do not know the source/supplier of the materials used in the shoes

2. The Industry Perspective on Meaningful Environmental Footprinting

The SAC and brands involved in the PEF Pilot support the overall objectives and vision of the European Commission’s PEF Pilot. An effective tool and approach should be developed that enables accurate and meaningful environmental assessments and communications about the environmental performance of supply chain members. Developing this requires engagement with all partners in the complex footwear value chain to ensure accurate environmental footprints. The SAC learned the critical importance of this through the development of a suite of tools, including: Product Category


Rules (PCR) for environmental footprinting of jackets, the Material Sustainability Index (MSI), the Design and Development Module (DDM), and the Facilities Environmental Module (FEM).

This suite of tools, known as the Higg Index (http://apparelcoalition.org/the-‐higg-‐index/ ) took five years to build, an investment of millions of Euros, and tens of thousands of volunteer hours. This investment was made to address the specific challenges associated with the limitations of LCA methodologies, tools and databases that the Technical Secretariat uncovered again while participating in this pilot – the largest of which is building the necessary ingredients to ensure scalability and credible results for all members (all sizes and types) of the value chain. Standardization will enable us to focus on sustainable purchasing and capacity building work that scales environmental performance.


C. Technical Insights and Recommendations

1. Data Availability (Facilities and Materials)

Data availability for facilities and materials has been challenging specifically as it relates to energy use, material taxonomy, life cycle inventories and qualitative material attributes. In outlining the challenges below we’ve included recommendations for how to improve data availability for both facilities and materials.

Facility Data Challenges:

Based on our PEF Pilot experience, there is an absence of consistent, comparable factory-‐level data and management practices information. Specifically:

While Tier 1 and Tier 2 energy use was identified as a hotspot in the LCA of a shoe, brands observed a general lack of data availability from the factories. Factories often do not have the resources and capabilities to report the necessary data. Most are unable to provide specific energy, water, waste, and other environmental data per material or product. As a result they need to estimate their energy and water usage data for this PEF Pilot based on invoices they receive from their utilities or from a single meter for their entire facility. Typically factories calculate the energy or water used per product by dividing the total annual water or energy consumption by the total number of shoes manufactured at their facility – this allocation method and any single approach, (i.e., allocation by size or weight of materials) produces results that often don’t match reality. One example of an issue with allocating per pair is that a sandal and a football boot will be shown to use the same energy in the manufacturing process, however the football boot consumes more energy during die cutting (more materials) and more time in the ovens (more materials to dry). Implementation of a data collection system that would track individual shoe style/SKU5 data is not possible for many reasons. A few examples include:

• Most factories only have one meter to measure water and one meter to measure energy for the entire site. There are no individual meters for each process within a factory.

• Sometimes factories do not have any meters for energy consumption. In those cases they only measure energy usage through the invoices they receive for the electricity, coal, diesel, and gas purchased.

• Every machine and process in a factory would need to be monitored to obtain style/SKU-‐level energy. water, and waste data.

• Typical shoe factories have more than 20,000 individual machines, making energy monitoring cost prohibitive. Data collection and analysis systems would need to developed for each factory, and have the capabilities to store and analyse several billion data points each month.



• Global management standards highlight overarching routines at the factory level, but do not provide information at the shoe style/SKU level. In addition, existing standards are not designed to compare products or factories, serving instead to drive overall management practices relating to energy usage.

Evaluating Energy Use:

For those factories that can report energy data, there is currently a lack of standardized methodology for collecting and calculating energy use per pair at the facility level. This leads to scope discrepancies between factories and brands. In the absence of a standardized and documented methodology guidance for collecting and reporting facility level energy use and pairs produced (to calculate the facility level energy use per pair), the data can be reported at different boundaries, leading to inconsistent and non-‐comparable results:

• Some factories reported only electricity and the main fuels used in the central boiler, but not the propane for forklifts and smaller heaters throughout the factory.

• Some factories did not include the energy use for separate warehouse facilities, offices, canteens and dormitories, while others reported total energy use for all facilities.

• Some facilities reported energy use and shoe production for an entire year, while others only had a few months worth of data.

• Some factories separated their energy use between two buildings (when one building does sandals versus another building does athletic footwear), leading to more specific data, whereas other factories reported overall average energy use.

SAC is working to address these challenges in the Higg Index by developing a full toolkit for factories to measure energy consumption in a consistent way, creating boundaries and normalization factors to get better data. Updates are still being made to increase comparability in the data. The tool is collecting data at thousands of factories, which improves data availability, analysis and verification for getting at more refined estimates for energy use per pair.

Missing Impacts:

Other factory-‐level environmental practices, such as certifications or hazardous waste management practices, are currently not captured with existing datasets and could be missing in PEF methodology, although they can drive significant environmental impacts. For example, it is important to capture whether a facility has wastewater treatment technology, as this could potentially drive the PEF results for the materials or products produced at the facility. Primary data that captures the impact of different waste water systems is largely missing right now and will be in the foreseeable future. Industry averaged data sets are the common data source for PEF calculations.

SAC has tried to fill these gaps using a qualitative approach to measuring practices that lead to impact reductions. The Higg Facilities Module uses this approach to capture these critical impact areas while it builds its primary unit process data in its LCA-‐based Material Sustainability Index (MSI). The two approaches are complimentary.

Table 1 provides a comparison of data needed for the Higg Facilities Module (FEM) from the SAC and the PEF methodology.


Table 1: Comparison of factory environmental practices included in PEF methodology and SAC Higg Facilities Environmental Module (FEM)

Environmental Impact Topic SAC Higg Facilities Environmental Module

(FEM)

EU PEF

Air pollutants (by source – e.g., stack, chimneys, vents)

Included as qualitative measures

Included. “Default” secondary data used as Brands do not have product-‐specific information

Air pollution treatment program and stringency level


Not explicitly included. If such programs demonstrate lower environmental impacts, that reduction would be considered in PEF method. Currently LCI databases do not capture the benefits of these programs

Wastewater contaminants Included as qualitative measures


Wastewater discharge volume Primary data collected and included for each facility


Non-‐hazardous waste generation Primary data collected and included for each facility

Included “Default” secondary data used as Brands do not have product-‐specific information

Hazardous waste generation Primary data collected and included for each facility


Non-‐Hazardous waste management (e.g., treatment technology)


Not explicitly included. If such programs demonstrate lower environmental impacts, that reduction would be considered in PEF method. Currently LCI databases don’t capture the benefits of these programs.

Hazardous waste management (e.g., treatment technology)


Not explicitly included. If such programs demonstrate lower environmental impacts, that reduction would be considered in PEF method. Currently LCI databases don’t capture the benefits of these programs

Fossil fuel consumption (coal, oil, natural gas, other)

Primary data collected and included for each facility

Primary product-‐level data were collected by Brands for Tier 1 only. For other Tiers, “default” secondary data is included as Brands do not have product-‐specific information


Renewable and non-‐fossil fuel consumption


Primary product-‐level data were collected by Brands for Tier 1 only. For other Tiers, “default” secondary data is included as Brands do not have product-‐specific information

Water consumption

Freshwater

Reused water

Included separately as Freshwater and Reused water consumption.



Greenhouse gas emissions release Scope 1 and Scope 2 Energy data collected for calculating greenhouse gas emissions


Third party certifications concerning environmental management such as Blue Sign, Oeko Tex, Leather Working Group, etc.

Included as qualitative measure with request for documentation


Chemical management program (MRSL and RSL)


Not explicitly included If such programs demonstrate lower environmental impacts, that reduction would be considered in PEF method. Currently LCI databases don’t capture the benefits of these programs

Environmental Management System (EMS) and associated audits



Environmental permits

Water, air, waste, other




Facility Data Recommendations:

Given this experience, we recommend leveraging the Facilities Environmental Module (FEM) of the Higg Index, which has been used at more than six thousand factories this year, and could expand to more than 10,000 factories next year. FEM collects quantitative data that can be used to calculate LCA impacts at all tiers of the supply chain, as well as qualitative information that can help to fill in data and gaps in LCA methodology. Manufacturers use the Higg Facility Modules to measure the environmental performance of their facilities. These modules measure impacts at individual facilities. Users conduct the assessments at least once a year and Environmental Module assessments are now being verified by SAC-‐approved and trained assessors on-‐site. Benchmarking by facility type allows facility managers to compare their performance against their peers. The module’s aspirational-‐level questions give manufacturers clear guidance on hotspots for improvement and outline the current best practices in the field.

The Facility Environment Module: This module is appropriate for any tier of manufacturing in the apparel, textiles, and footwear industry. It measures: Environmental Management Systems (EMS), Energy use and greenhouse gas emissions, Water use, Wastewater/effluent, Emissions to Air (if applicable), Waste management and Chemical use and management

Verification Pilot Program: To increase the robustness of the Higg Index’s Environmental Module, the SAC launched a pilot program in 2015 to create and test a methodology for verifying self-‐assessment scores. Building consistency and credibility of scores builds trust in Higg Index data, and this helps partners across the value chain to make better sourcing decisions. It dramatically reduces the need for multiple, separate audits, which frees up manufacturers’ resources so they can be directed towards actual capacity building and making improvements. Importantly, it also shifts the mind-‐set from compliance to performance improvement. Verification is performed on a first come, first served basis for SAC members who submit their factories for verification. It is completed by SAC-‐approved verifiers who evaluate, either on-‐site or off-‐site (facilities choose which approach they prefer) factories’ programs, documents, or results. The goal of this pilot is to verify at least 200 manufacturing facilities. Lessons learned have helped inform the design and implementation of an updated program

Additional information regarding these tools can be found at: http://apparelcoalition.org/the-‐higg-‐index/.

Material Data Challenges:

Brands, factories and material vendors lack a common, consistent and standardized system to identify material contents and manufacturing processes, leading to brands guessing about the contents and manufacturing processes of their materials.

Brands do not have access to comprehensive and consistent life cycle inventory data for the numerous material manufacturing processes involved in their supply chains. Fashion brands develop new materials and respond to trends quickly – so quickly that traditional LCA datasets might not be representative of the materials they use. Materials are very complex and diverse. There is large variability between brands of what is considered the “same” material. An example of inconsistent and non-‐representative materials level data in Brands’ databases is Polyurethane (PU) Synthetic Leather. This material, sometimes referred to as faux leather, PU leather, or pleather, is one of the most used material types in footwear construction, but also one of the most complex and variable. It is a composite layering of polyester, nylon, polyurethane, and other materials. There is no single PU Synthetic Leather formulation that accurately captures the complexity and variability in different PU


Synthetic Leather sub-‐types within the footwear industry. Different brands use different compositions to create different PU Synthetic Leather materials. Unless brands have a detailed understanding of their PU Synthetic Leather used in each product, calculated PEF scores for footwear are limited to a generic PU Synthetic Leather input, which can be inaccurate and non-‐differentiating. Table 2 below captures each Brand’s interpretation of average PU Synthetic Leather material used in its products.

Table 2: Synthetic leather assumptions (per kg by weight)

Brand A Brand C Brand D Brand E upper

Brand E lining

Polyurethane 20% 60% 20% 75 % 30 %

Polyester 20% 20% 80%

Recycled Polyester

20%

Nylon 6 40% 20% 70 %

Other…? 12.5%

Material Data Recommendations:

The Materials Sustainability Index (MSI) can address the gap between getting from material name to material content and manufacturing processes. This gap must be bridged in order to evaluate the environmental impact of footwear materials.

The MSI offers: • A material taxonomy that serves as a common language across the industry to identify and

track material contents and specific manufacturing processes, • A taxonomy that allows for material innovations to easily be incorporated for staying relevant

in a fast moving industry, • Cradle to gate life cycle impacts of commonly used materials and manufacturing processes

using LCA and methodologies consistent with PEF, • Qualitative measures to fill the methodology gaps for harder to measure impacts such as

toxicity identified in both our screening and PEF supporting studies.


2. Brands’ Internal Product and Material Systems and Product Composition Information

There are no standardized systems or databases for brands to manage and track their products and materials. There is much variability regarding the visibility and access that brands have to product and supplier data. Some brands do not have any systems at all and others use a variety of different systems or spreadsheets throughout the company to track basic product and material data.

Most existing systems and spreadsheets do not include complete information on the material composition, weights, and other data required for a PEF product environmental assessment. Often these systems do not include all of the materials that are actually in the product.

Many brands have invested in a number of different systems over the course of their business changing and growing. Sometimes product and manufacturing data sits in excel, SAP, access databases, legacy software systems, etc. Ensuring the data across these systems is complete and uses consistent nomenclature is a daunting task, so most brands will not invest in a single place to keep Bill of Material (BOM) details.

Table 3 provides an example of the variability of material-‐level data available from several brands that participated in the EU PEF Pilot. The first column in the table includes an example of the data needed for one sub-‐component of a shoe and the ideal granularity of data attributes needed to accurately assess its life-‐cycle environmental impacts. The subsequent columns indicate the level of data available in each Brand's existing databases for managing and tracking the materials in their shoes.

Since raw materials and the associated processing are the two main drivers of overall PEF impact, detailed information about the weight of each shoe component is crucial to the success of any LCA-‐based evaluation. In general, heavier products require more raw material inputs than lighter shoes which serve the same function. The upstream production of these raw materials requires more energy, resources, water, chemistry, etc. in processing and manufacturing. There are certainly nuances to this point – e.g., heavier products may be more durable, and some lightweight materials can actually have higher impact per kg than some of the materials they replace. There’s no simple answer, but all else being equal, a heavier product will always have a worse environmental impact. Most brands lack crucial information about both how much and which materials are in their products, leading to serious difficulty conducting environmental product assessments.


Table 3: Availability of material-‐level data in brands' databases

Data availability, by brand

Data Needed Examples Brand A Brand B Brand C Brand D Brand E Brand F

Shoe Part Name Vamp, counter Partial Partial Yes Yes Dispersed Not available

Material Type Textile, foam Partial Yes Yes Yes Dispersed Not available

Material Name Spenco, Ortholite, Merry Mesh

Partial No Yes Dispersed Dispersed Not available

Material Content Polyester 90%

Elastane 10%

Dispersed Partial Partial Yes Dispersed Not available

Material Yield 0.2 Linear Yards Partial Partial Partial Dispersed No Not available

Material Weight 15 g/sqm Dispersed No No No Dispersed Not available

Textile density (denier or dtex)

40 denier Dispersed No Partial No No Not available

Material construction process

Knitted Dispersed Partial Partial Dispersed Partial Not available

Material attributes Batch Dyed, water repellent finish

Dispersed No Partial Partial No Not available

Tier 2 Material Supplier Name

Li Feng, San Fang Partial Partial Dispersed Partial Dispersed Not available

Geographic region of Tier 2 Material Supplier

China Partial Partial, Dispersed

Dispersed Dispersed Dispersed Not available

Geographic region of Tier 2 material production facility

Vietnam Partial Partial, Dispersed

Dispersed Dispersed Dispersed Not available

Key indicators:

Yes: Brand has complete and accurate information, in “main” Bill of Material (BOM) system or file.

Partial: Brand only has partial information (e.g. only data for some parts of the shoe, not all), in “main” BOM system or file.

Dispersed: Brand has information, but in a different system, database or file from the “main” BOM system or file (e.g. materials database, costing database), which generally will present complications to link to each BOM part, and generally will not be 100% complete.

No: Brand does not have the information.


Brand B

Table 4 below illustrates that the level of material data required by the PEF methodology does not exist in Brand B’s systems. Many of the materials actually in a Brand B shoe are not included in their systems. Only the noticeable materials in the upper part of the shoe and the outsole of the shoe are accounted for in Brand B’s systems. Weight and other material/component data are not captured in any of Brand B’s systems.

Brand B typically only has business relationships with their Tier 1 shoe suppliers (the final assemblers of the shoe). Brand B currently has little transparency of their Tier 2 and 3 shoe suppliers (the producers of the textiles, leather, rubber, etc.). Materials originate from many different Tier 2 and 3 suppliers.

For this PEF Pilot Brand B’s Tier 1 suppliers were required to reach out to their Tier 2 suppliers. All data on the materials had to be collected manually for the PEF pilot, as is common practice while conducting an LCA. Brand B had to request that their suppliers send samples of the materials that make-‐up the shoes. Many of the components that the Tier 1 supplier collected and sent to Brand B for this pilot were often already processed (e.g. glued together). In order to obtain the weights of the individual materials, the components were torn apart and then weighed by Brand B staff. In some cases that was not practically possible and the weight of the individual materials had to be estimated, often by simply dividing the total weight by two.

Table 4: Example of the limited data available for a Brand B shoe

Placement Type Description Appearance Composition Qty/Construction

Qty/ Consumption

Weight Supplier info

Shell

SHOE Other VR-‐HM-‐8023…

100% POLYESTER

0.18 yd. (54.00 in)

SOLE Other 100% THERMOPLASTI…

Lining

SHOE Other IMITATION FUR

0.15 yd.


Image 1: Actual components in a Brand B shoe provided by Tier 1 supplier for the pilot

Brand C

Table 5 is a snapshot of approximately one-‐fifth of an entire BOM for a Brand C shoe. The BOM does not include specific information regarding material composition, manufacturing processes, or weight per component. Suppliers dismantled the shoes and weighed each component for the PEF Pilot. However, the suppliers were not able to provide sufficient or correct material composition and processing methods for the PEF Pilot. As a result, Brand C was required to make assumptions and estimates to complete calculations for obtaining Environmental Score Labels.

Table 5: Example BOM for a Brand C shoe (Note: this table represents a snapshot of a BOM for a Brand C shoe; actual BOM for shoe includes approx. 5 times as many rows/materials)

Part number Part Name Material

1 UPPER UNIT ASSEMBLY

5 TOE CAP ASSEMBLY

40 Toe Box WINMELT 2010 0.15MM 40-‐1 Flat HP

240 VAMP ASSEMBLY XTEX 158

420 Vamp

420-‐1 Xyarn 950D

420-‐2 Dyed 600D


420-‐3 Dyed 300D

420-‐4 Eyestay Punching hole

420-‐5 Eyestay HF HF DEBOSS

420-‐6 Steel Cut

480 Vamp Extension

480-‐1 Tricot TRICOT 36 G

480-‐2 Foam FU 50

480-‐2 Foam 2.00 MM

480-‐3 Self-‐Adhesive SELF ADHESIVE

480-‐4 Lamination LAMINATION CANVAS TC MESH + FOAM

500 Vamp Lining XMF

515 Vamp Lining Reinf. XMF

550 Vamp Overlay UNICO FLEX FROST

550 Vamp Overlay METAL

550 Vamp Overlay ENAMEL (P 000 WHR)

550-‐1 Fading Graphic Print PRINTING SCREEN

550-‐2 Dot print PRINTING SCREEN

550-‐3 Vacuum Forming

550-‐4 For AQ3109 MODE effect TPU UNICO FLEX FROST

550-‐4 For AQ3109 MODE effect TPU

LINE 1 DM (P 746 WMA) 550-‐4 For AQ3109 MODE

effect TPU MODE

550-‐5 For S79625 normal TPU

UNICO FLEX

550-‐5 For S79625 normal TPU

UMT 2 (P 000 WKD)

550-‐6 HF edge HF DEBOSS

620 Vamp Reinf. FU 50

620 Vamp Reinf. 2.00 MM


Brand E

Brand E found that it was difficult to obtain information on component weight and composition. While Brand E has good transparency into their supply chain (both tiers 1 and 2 as well as sub-‐suppliers and sub-‐component suppliers) they do not have any systems in place to track the composition or weight of shoe components. Brand E only has composition information for the main material used in the upper portion of the shoe and the sole. Weight is not tracked by product, they only track the total quantity of materials purchased by season or year.

Obtaining the level of detail needed for the PEF took 5 people 8 days of accumulative work – data collection was spread out over 4 months. Brand E determined that it would be nearly impossible to manage this level of data collection on a regular basis. They do not have systems or personnel in place to collect and manage this level of data.

Brand E’s suppliers are small and it is difficult for them to manage data requests like the ones needed for the PEF Pilot – they have to stop production work and manually weigh and collect the information. It is not currently feasible for the suppliers to implement this at a larger scale.

Additionally, Brand E does not have anyone on staff that is experienced in LCA work and found using the PEF calculator very complicated. In order to ensure that they were able to accurately use the tool Brand E had to hire a consultancy for additional support.

Brand E also noted that while it was difficult for them to collect the level of data needed for the PEF pilot that it was easier for them than most brands of their size. Brand E regularly reports and monitors the environmental footprint of their materials and suppliers and have good transparency through their supply chain. From their experience working with other brands of their size or smaller they noted that this is not generally the case.

Image 2: Actual components in Brand C shoe provided by Tier 1 supplier for pilot


Material Systems Recommendations:

Addressing the challenges listed above will require investments by brands, manufacturers and technology systems providers over the next decade. Industry collaboration is absolutely crucial to fill the information gaps. Pilot testing brands recommend the following solutions:

• Creating a common materials taxonomy: SAC’s Materials Sustainability Index (MSI) has started

to create consensus around the materials taxonomy for footwear materials. The MSI offers a material taxonomy that serves as a common language across the industry to identify and track material contents and specific manufacturing processes. This taxonomy is not only essential to sourcing offices that capture materials data in Brands business systems, but also for software providers that create and enhance the product design software that brands use to create and track technical specifications throughout the product life cycle.

• Build default assumptions, where appropriate, based on a large primary data pool to ensure scalability of measurement for small brands, or brands who are building their knowledge of their supply base. This pilot created default assumptions by averaging primary data provided in the pilot; this somewhat small data pool was based on just the dozen or so shoes evaluated in the screening, with some data points like chemical emissions only provided for one or two shoes. These defaults were then integrated into the PEF Calculator tool so brands could either use their own primary data or rely on defaults where needed, especially for areas of the life cycle which were not shown to be hotspots (e.g., retail).

• Build primary data sources: Create a materials database where material suppliers are incentivized to submit materials data. MSI provides a well developed taxonomy and robust quality assurance process to ensure comparability of data. They are able to create material scores that they can share with the public and their customers directly; saving brands from several of the tedious processes listed above.

3. Methodology Challenges

There are significant methodological and scientific barriers to the application of general toxicity criteria within a life cycle impact assessment (LCIA). Currently, all methods evaluated in the International Reference Life Cycle Data System (ILCD) handbook for the assessment of the fate and effects of metal and chemical compounds, including USEtox, suffer from a lack of precision (i.e., a large uncertainty of 2 to 3 orders of magnitude). Therefore, the USEtox characterization factors for metal and chemical compounds6 are rated as interim and should only be used with caution and not for product comparison and product labelling.

In addition to uncertainty in the characterization factors within the LCA methodology, there is also the issue of addressing the scope of toxicological damages. Toxicity impacts are very localized environmental impacts. Since LCA takes into account business at a steady state, normal operations are assumed with geographic and industry averages. The LCA community has built powerful tools to

6 The USEtox characterization factors for metal and chemical compounds can be found on the USEtox website


capture many industrial processes around the globe, but the inventory datasets that include toxicity emissions will likely never be so local in scope that toxicity evaluations could provide meaningful results. For example, an emission of lead to a slow-‐moving water system in a heavily populated area would have very different toxicity effects on health and the environment than lead emitted far from civilization. LCA measures impact on a macro-‐economic level, whereas toxicity affects people and the environment at a very local level.

The international scientific community and other stakeholders are working on the toxicity LCA methodology issues. Additional work could further improve the assessment and communication on the environmental footprint of products. There is a call for further discussion and action with relevant parties to share priorities with the common objective of helping to accelerate the development of more robust methods to evaluate toxicity.

However, the exclusion of toxicity from the benchmarking and single score calculation7 is not a reason to ignore it all together. There are chemicals used and emitted through the textile supply chain (especially in dyeing and finishing), which have been flagged as potential hazards and are not always treated or disposed with the appropriate safety measures.

Additionally, emissions from fires, unauthorized or illegal activities, natural disasters, etc. are all outside the scope, so issues like illegal wastewater dumping will never be considered. Identifying best practices in the supply chain could provide some context to the toxicity story since many of the uncaptured emissions happen deep in a complex supply chain outside the planned operations.

Methodology Recommendations:

To fill the gaps identified above a qualitative approach should be used to assess chemistry impacts while developing improved quantitative measures and datasets. Existing initiatives that could be leveraged include:

• The Zero Discharge Hazardous Campaign (ZDHC), a well as the Materials Sustainability Index

(MSI) from the SAC. Both offer qualitative measures to fill the methodology gaps identified in both our screening and PEF supporting studies for harder to measure impacts such as toxicity.

• Leverage the Facilities Environmental Module (FEM) of the Higg Index: the industry is coalescing around the FEM for facility-‐level assessment of environmental compliance, impacts as well as management practices.

4. Durability

Increasing product life by improving durability, both in terms of construction and consumer practice, reduces environmental impact significantly. Capturing durability is material for assessing the life cycle

7 Several impact areas where not included in the benchmark because of their limitations. The PEFCR Annex IV describes why we excluded these other categories


impacts of footwear; however measuring it in a consistent and meaningful way requires additional work above and beyond the timeframe and capabilities of this pilot.

Durability Measurement Challenges:

The PEF Pilot experience has surfaced challenges related to quantifying the lifetime of shoes. For example, footwear is segmented by more than 100 different categories and sub-‐categories (e.g., running shoes vs. fashion shoes vs. outdoor shoes, etc.). Different shoe sub-‐categories have very different definitions of durability or lifetime (running counts in miles run, luxury in terms of years kept, football in terms of hours played). Some shoe categories have health and safety requirements that impact durability.

Innovation in the athletic footwear industry is traditionally directed at producing lighter products to enable athletic performance and help athletes achieve their maximum potential. This may also impact durability.

Furthermore, it is important to understand durability in the context of The Consumer Guarantees Directive, so that there is no risk of litigation involving shoes that are not defective.

Finally, testing practices for quality vary by company. Each brand has adopted different testing standard protocols and machinery to test for the quality product. This would require alignment around common standards. Once agreed, these new standards would then require fundamental changes in the brands’ entire supply chains from design to manufacturing, which will come at a cost that could be transferred to consumers.

Durability Recommendations:

Incorporating an effective quantitative measure of lifetime of shoes in a PEF score will require additional work, time, and resources beyond those available for this round of pilot projects. Additional research is needed to fully evaluate:

• How to create like categories of products for comparison on durability where relevant and feasible and define a measure of durability within each category

• Potential impacts of the proposed durability requirements with respect to laws already in place such as the Consumer Guarantees Directive

• Common test methods or equivalencies (e.g. equivalencies to the test methods proposed in the Grenelle methodology) that could be applied with brands and suppliers infrastructure

As these areas are explored in greater depth, durability can be evaluated with qualitative indicators such as those used in the Higg Index Design and Development Module.

5. Scope of Benchmark Grades (A-‐E) for Footwear Categories Tested

Benchmark classes do not adequately capture product-‐level differences. Early in the pilot, the Technical Secretariat considered multiple product classifications and benchmarks. Due to complexity and time constraints, it was determined to run the pilot with one classification to focus efforts on improving the scoring methodology and data requirements.

Therefore, the development of the PEF Benchmark classes is based on a limited range of styles, sizes, and product types that represent only a fraction of the entire footwear universe.


Figure 2 below from Brand A illustrates that the thresholds for scoring A through E worked well for running shoes, however the thresholds do not provide enough differentiation for boots or sandals.

Each point in the graph represents one product style. • Various Brand A running shoe styles received scores ranging from A through E • Various Brand A sandal styles only received A and B scores • Various Brand A boot styles only received D and E scores

These results highlight the need for different thresholds by shoe category. Otherwise, with only one general PEF Benchmark class, the PEF letter grades are mostly driven by the weight of the shoe. This factor is inherent to product type – for example “boots” are heavier than “sandals” and will therefore always score lower.

Figure 2: Differentiation and lack of differentiation of scores for Brand A running shoes, sandals and boots


Brand C also conducted several scenario analyses, replacing conventional materials with ‘environmentally preferred materials’ for the materials in the shoes using the Detailed BOM approach in order to determine whether more ‘sustainable’ materials would show differentiation in scores (see figure 3 below). Scores for the shoes did not change with the material substitutions – this could be a limitation of the PEF Calculator tool, or this could be the result of a ‘green’ material substitution that does not have the assumed environmental benefit. In order to test which scenario is actually happening, the tool could be updated to include material choices with the granularity to differentiate between conventional and environmentally preferred materials (EPMs). Details of this can be seen in figure 3.

Figure 3: No change to scores for Brand C shoes using Detailed BOM tool when conventional materials were replaced with environmentally preferred materials (EPMs)

Recommendations:

• Option 1: Establish additional shoe categories and redefine more specific benchmark classes: an appropriate balance of product categories needs to be created to reflect differentiation of similar products. This will need to be developed and refined as we perform environmental footprints on more and more shoes.

• Option 2: Communicate an actual PEF normalized footprint value instead of a letter grade. • Option 3: Consider alternative to scoring at a style level such as whether a manufacturer has

adopted and reports using a bona fide environmental system such as Higg.

The Brand B shoes pictured in image 3 below are considered to be in the same category (Sport/Leisure/Fashion) in the PEF Pilot. The weight of the shoe was the greatest factor in the resulting score – the heavier the shoe the worse the score (e.g. the heaviest shoes receive an E). As evident in the pictures, these products are very different from each other. It would not be relevant to compare these products environmental performance score since customers would not choose between a heavy insulated boot (top left) and light pumps (bottom right).


6. Scalability challenges

The volume of data needed for a differentiating score is very detailed and beyond what most brands have access to in their normal course of business.

Simple BOM

We evaluated whether simple BOM information could be used for brands that have limited access to materials and product related data. This can include small to medium size brands as well as brands that source finished products directly from factories.

The scores calculated with actual shoe composition and weight (also known as Detailed BOM) are not comparable with results of shoes modelled with the Simple BOM. Brands who tested their actual shoe BOMs and the Simple BOM approach saw different scores for the same product. If brands are allowed to use Simple BOM, they will be creating a set of low quality results that would potentially undermine the overall effort and could create unintended consequences.

The scoring system is not sensitive enough to measure and reflect environmental performance. Brands found that there was a lack of scoring differentiation using the Simple BOM default values (e.g. all products receive the same or very similar scores). In addition, the single broad shoe category leads to “low resolution” of A-‐E scores. The most significant factor impacting the scores was the weight of the shoe – the heavier the shoe the worse the score (e.g. the heaviest shoes receive an E). Table 6 below illustrates that the Simple BOM produced the same score for several Brand C shoes that scored differently with the Detailed BOM approach. All the shoes shown in table 6 use multiple conventional materials (not environmentally preferred materials), and were of varying weights.

Image 3: BRAND B shoes grouped into same category in PEF pilot


Table 6: No variation in Brand C shoes using simple BOM. Simple BOM methodology results in worse scores compared to detailed BOM

MESSI 16.3 TF J (kids)

X 16.3 FG J (kids)

X 16.3 TF J (kids)

MESSI 16.3 FG J (kids)

MESSI 16.3 IN J (kids)

Net weight (g)

490.4 350 416 441.4 456.4

Detailed BOM

B A B B B

Simple BOM C C C C C

Default Tier 1 and Tier 2 energy use

Manufacturing energy defaults are not representative for all products

Using default energy values for Tier 1 and Tier 2 suppliers reduces the differentiation of scores, and in some cases results in better product scores compared to using actual values. This creates 2 issues:

• Lack of differentiation for shoes that actually have significantly different footprints • Incentive to not use actual values in some extreme cases, leading to artificially better scores

for some shoes

See Table 7 below for a comparison of default values versus actual measured values.

Table 7: Supplier default values versus actual measured values

PEF Scores distribution for different Tier 1/Tier 2 energy use per pair scenarios

Scores Number of Shoes (using default values)

Number of Shoes (using actual measured factory-‐specific values)

A 0 2

B 11 6

C 17 9

D 5 7

E 0 1


Recommendations

Brands following the PEF scoring methodology should be required to use actual BOM information and actual Tier 1 and Tier 2 energy data. However, that energy data is not currently available to most brands as part of their normal course of business today as evidenced in the data challenges section.

7. Scalability, Resources and Costs

The resources required to collect and process the detailed data and calculate PEF scores are significant and make it extremely challenging and cost prohibitive for brands to scale to their entire product range. Substantial investment in process redesign, human resources and information systems would be required by brands and the supply chain to scale the EU PEF scoring methodology to all product styles/SKUs8. The PEF methodology would require:

• Significant modification to brands’ internal processes and technology systems for data collection, review and verification

• Materials and manufacturing suppliers to create new systems and processes to collect and manage the detailed data needed

The following summary provides examples of the types of costs and resources based on the piloting brands collective experiences:

• The piloting brands reported a range of 2 to 9 hours to score a single product style/SKU. This is a significant time investment given that larger Brands can have up to 20,000 SKUs o Process included data collection (e.g. weight, construction, material type, energy use, and

water consumption) from suppliers, data review, statistical analysis, and time for verification or gut check.

o The estimated hours only includes the number of hours for the brands. It does not include amount of time incurred by materials and manufacturing facilities to collect and upload information. Manufacturing facilities estimated at least 2 hours per product to collect the data needed. This included stopping production and manually weighing each material and collecting the required information. The material suppliers were not able to provide estimated time per product.

• Examples of the brands’ staff required to be involved for data gathering, review and verification include:

o Sustainability directors, managers, analysts, and compliance staff o Footwear developers, material developers, engineers, and liaison staff working with

materials and manufacturing supplier facilities • Estimated cost for information systems development and implementation needed to scale the PEF

scoring methodology range from $2M USD to several million USD; including a lengthy development period requiring fully dedicated resources. The yearly costs for maintenance, upgrades, hosting, and licensing fees range from $100,000 to $400,000 USD.



o These estimates may change depending on costs for LCA database licensing o These estimate do not include costs of information systems development required by

manufacturers and materials suppliers • Significant investments will be required both at the Brand and manufacturing facility level for

verification

Recommendations:

Leveraging industry-‐wide efforts/tools like SAC’s Higg Index, which already standardize measurement in the supply chain and collects vast amount of primary data, would help to make the process easier over time. However, for any type of detailed reporting about product level information, brands and suppliers will also need to invest heavily in their own systems, expertize and processes. This investment would ultimately be borne by consumers. Many small and medium size brands may not be able to pass this cost along while maintaining their current business model. This will result in an uneven competitive landscape, poor data integrity and lack of confidence.


D. Communications Vehicle and Testing

Pilot participants are currently testing the communication vehicles. The information shared in this chapter focuses on initial findings from focus group testing and market test by a single participating brand. This brand started testing the communication vehicle as of May. Please note that these initial findings do not yet represent the final conclusions of the PEF Pilot for non-‐leather shoes.

The main goals for the Footwear PEF Communication Vehicle are to contribute to more sustainable consumption overall by helping consumers make more informed choices on the products they buy; increasing the attractiveness of products with a better PEF score; and improving the environmental performance of individual products through improved product design and increased competition for performance across a level playing field.

With the above goals in mind, the Technical Secretariat developed a multi-‐layered approach to developing and designing the communication vehicle and market testing approach utilizing existing behavioural insights on the successful communication of environmental information for consumers, including the Commission’s own background document. The resulting Communications Vehicle was based around (but not limited to) a simple performance label (image 4). For more detail on the process and rationale, please refer to the PEFCR report.

In order to test the effectiveness of the Communications Vehicle and support the objectives of the PEF pilots, third party communications advisers Salterbaxter and the Technical Secretariat developed hypotheses and a methodology for the communications test to answer these questions. This includes both market research in the retail store environment, out-‐of-‐sales-‐environment focus groups and observational insights across multiple EU countries. For the full methodology and approach, please refer to the PEFCR report.

Image 4: PEF performance label


1. Communications Test: initial qualitative insights from focus groups

At time of writing, only the feedback from the focus groups conducted out-‐of-‐sales-‐environment was available for evaluation. As this is qualitative data involving a small sample size these preliminary insights against our developed research questions should be interpreted with caution. We do not draw any final conclusions at this stage. The findings will be updated with the results of the further research undertaken during the rest of the pilot.

Consumer understanding of the PEF Communications Vehicle

The scale (A-‐E) is intuitive and simple but lacking in the detail. Consumers understand A is best and E is lowest.

Consumers’ evaluation of the PEF Communications Vehicle

The label communicates that there is an environmental impact but fails to clearly illustrate what that impact is. Consumers associate an ‘A’ rated shoe as being hand made, from ‘more natural’ materials. Consumers associate an ‘E’ rated shoe as being a plastic, cheap fashion-‐shoe made in sweatshop factories in Asia. However, some consumers believe that the ‘In association with the European Commission’ statement implies that the product has been made to European Union standards, rather than the label being a European Commission’s initiative itself.

“It doesn’t tell you what the difference between A and E is”

Respondent in the UK, 18-‐25 group

“It is easy to interpret. A is the best and E is the worst. But I don’t see how a shoe can be A or E”

Respondent in Spain, 18-‐25 group

Examples of environmental impacts in footwear manufacturing in the Level 2 communication, provided as stimulus material, successfully make a tangible connection with consumers. But there will be an understanding gap for consumers that do not make the effort to obtain the Level 2 communication.

How the PEF Communications Vehicle influence consumer perceptions (of product and brand)

A limited understanding of what factors make up the score contribute to contradictory interpretations on performance. Some consumers see higher scores as being more expensive, using local materials and associate it with being more handmade than mass-‐production. However other consumers feel that cheaper brands may have higher scores because the materials used are simpler, with fewer production processes and phases.

Brands who take interest are likely to generally be viewed positively – they are showing interest in investing in a better world and ‘doing their bit’ to help. Consumers suggested that those with lower scores would strive to improve in order to retain competitiveness.

There was a small element of cynicism that the label would be a greenwashing initiative.


“It will encourage brands to think about how they are making shoes”


“The beauty of this system is that brands would be pushing each other to get As and that would lift the bar more and more and we will all benefit from it”


How does the PEF CV influence consumers’ attitudes? (connection and interest in environmental issues)

Consumers have difficulty understanding how shoes can impact the environment when prompted, consumers are unable to identify where in the footwear lifecycle process might be the most negative environmental impacts.

“A washing machine consumes power and water… shoes don’t consume anything”


“I never thought about it with shoes. But I do check clothes tags to see if it’s made in Taiwan or China … if it’s made in Poland, then the conditions are more humane.”

Respondent in Poland, 18-‐25 group

Consumers agree that the environment is important to consider, however the label raises questions around why social aspects – which are more commonly understood – are not included.

“They forgot to add information about employing minors in the places where they make shoes.”


Influence of the PEF CV on consumers’ behaviours (purchasing decisions, use/disposal of the product)

Decisions on shoe purchases are primarily based on aesthetics, comfort, performance and affordability. Brand and functional attributes are crucial factors in choosing shoes. Information about their impact on the environment is not sought or even considered.

Environmental factors are not a priority when shopping for fashion products, such as shoes, handbags and clothing.


“Look is really important for shoes and it has to be comfy”


“Shoes are definitely about design for me, they should be trendy, have the right design and also be good quality”


A minority felt that the label would have an influence on their shopping habits and that they would favour a brand or product with a higher label.

“If I was in love with a pair of shoes and they were an E rating, I would still buy them”


“I’m going to be very honest… I would not even look at the label. I am going to buy what I like, irrespective of the environmental impact”


2. Preliminary insights from brands in progress of market testing:

The following are preliminary insights from the single brand that has completed their market test, and do not necessarily reflect the other pilot brands who are still in the process of market testing. Insights from additional brands will be provided in subsequent reports.

Presence of intentions-‐behaviour gap

Intentions: • Customers ‘like to see’ these types of environmental initiatives from Brands • Customers say this type of communication vehicle (e.g. label) may influence their future

purchasing behaviours and perceptions of brand

Behaviours Observed: • Customers consistently communicated they prefer style, quality, brand and product

performance over environmental scores • Sales data for online and brick-‐and-‐mortar stores show that label doesn’t influence Brand

A store customers in their purchasing of running shoes (i.e. D and E rated products sold as expected similar to A-‐C rated products) Sales data for online and brick-‐and-‐mortar stores show that label doesn’t influence store customers in their purchasing of running shoes

• Observations showed that the vast majority of times the label was overlooked. Consumers did not spontaneously engage with the brochures at point of sale or near shoe wall. Nor did they seek further information about the labels. Consumers often cited recyclability and social factors when asked to define meaning of 'environmental score'


• It is easier for consumers to understand a 1:1 relationship (e.g. C score because of C level energy efficiency). However, the consumer loses the connection to the environmental score when there is a one score derived from amalgamation of many factors.

• The ‘what’s in it for me’ factor was lacking for the consumer when choosing shoes based on aesthetics, price, comfort over environmental scores (e.g. equivalent of energy efficiency financial benefit for shoes)

One key observation to stress is the lack of consumer understanding of the one-‐to-‐many relationship in the environmental score. Even though consumers understand an A grade being best and E being worse, there is confusion of what drives the A or the E, as depicted in the picture below:

As the ‘Environmental Score’ is composed of numerous factors that don’t have a direct relationship to the score, the explanation ‘loses’ the consumer. Once this relevance is lost, it is difficult to create a connection that gets them to think about how they can make a difference. If consumer behaviour is what the EC is trying to change, there has to be a direct connection of the score to the impact to allow consumers to feel empowered to make a behaviour change.

Recommendation:

Recommendations on the communications will be included in the final report, pending completion of market tests.


E. Harmonization Across European Initiatives

We commend the European Commission for organizing the PEF pilots and seeking to harmonize methodologies and initiatives in the footwear and apparel industry, promoting consumers’ awareness and more sustainable products in the market. The SAC and brands participating in the pilot support these goals through active engagement and collaboration. Through the PEF pilot, we see inherent value in a standardized approach to measure and communicate sustainability performance and recognize the significant challenges created by inconsistent data, processes and tools.

The SAC and PEF participants welcome the European Commission’s efforts leading to further transparency, specifically through the PEF pilot project, the Circular Economy Package and the European Garment Initiative. These efforts mirror the SAC 2020 vision, which is “Consumers choose products based on trusted sustainability information”.

We have observed overlap in scope and work and encourage alignment between these various initiatives to meet this common goal of harmonizing approaches, standards, and communications. Scope alignment will help the industry to focus their resources on a common approach for holistically and consistently measuring and evaluating brand, product and supply chain sustainability performance.

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