Research
Evolving sustainability metrics:
How theoretically applicable and technically feasible are Key Fitness Indicators (KFIs) for global apparel companies?
Future fitness provides a universal benchmark based on twenty one KFIs. These KFIs are potentially transformative in that they start at tomorrow's required practice as opposed to today's best practice. The KFIs build on leading research of the environment, systems, and social science. They cover a wide range of metrics from physical (e.g. energy, water, waste and production) through to indicators on employees, communities, and society as a whole. If we, as a society, want to evolve from creating business value to creating system value our metrics must also evolve based on our best understanding of the system. KFIs seek to redefine how we think about business, by capturing all of the ways in which a company can create system value.
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The Future-Fit model is holistic and not industry specific which allows for a potentially powerful bench marking tool. In order to achieve that potential, however, the model needs to be populated with data. I identified a specific research gap in utilizing the framework within an apparel context. Combining the KFIs across the full apparel supply chain yielded a more applicable model. I then identified where the intersections between the business goals and supply chain processes were most relevant/ material.
Systems thinking is a shift away from a simple cause and effect event based model. It goes beyond what or how something happened to understand why it actually occurred. This can be seen in the iceberg model at right.
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Future fitness was born from first understanding the current system we operate in and then identifying leverage points for change towards a new system. Increasingly, we have a better picture of the broader systems context that businesses operates in. Companies can no longer afford to operate with an outdated map of the world.
My research lies at the convergence of data analytics, apparel supply chains, and the Key Fitness Indicators (KFIs) as outlined by the Future Fit Foundation.
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Future fitness is a way to understand, define, and measure what a successful business must look like in the years and generations to come. It is a holistic set of 21 goals and indicators that can be used across industries to benchmark performance. We, as a society, urgently need to recaliberate what "business as usual" means. In order to do this successfully our underlying mental models need to evolve from a linear make-take-waste mentality towards a deeper understanding of the broader system that business operates in.
Open Research
Methodology
Milestones
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Engage with with the real world situation.
My first year of research was focused on investigating these questions:
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How is software currently being used to enable sustainability managers for global apparel companies to measure and manage their supply chains most effectively?
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can industry level organizations utilize software and anonymous data to bridge the “sector gap” and standardize innovations in supply chain sustainability across the apparel industry?
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Download my final research deliverable
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CYCLE 1: Create a future-fitness apparel model and populate with data
Reflect: Complete a literature review
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Act: I created this website and developed the Future Fitness of Apparel Supply Chains landscape model
Collect Data:
Research Companies and compile list to survey/ interview (n>20)
Build survey structure:
Populate each individual intersection between future fitness goal and supply chain process data in my model (1-5 scale)
Materiality: How material is each intersection to my company?
Starting point: Where does my company stand in terms of current initiatives/ corporate strategy?
Impact: How impactful would focusing resources on this intersection be?
Implementation Difficulty: How difficult would it be to get this data?
Analyze Data: Anticipated February 2017.
Reflect: Anticipated March 2017
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Cycle 2 (Proposed): Based on landscape analysis cause positive change
Plan: Based of the landscape analysis completed in Cycle 2, my research will either deep-dive into a single intersection of my model across multiple companies or work collaboratively with a single company. If I collaborate with a single company I will seek to analyze their current Key Fitness Indicator (KFI) performance.
Act: This is dependent on the theory that emerges from my inductive approach of Cycle 1
Collect Data: Anticipated April 2017
Reflect: Anticipated May 2017
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Final Deliverable: Dissertation - Anticipated June 2017
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I have chosen to utilize Participatory action research (PAR) as my methodology. PAR is an approach to research that emphasizes participation and action. It seeks to understand the world by trying to change it, collaboratively and following reflection. It emphasizes collective inquiry and experimentation grounded in experience and social history.
Data (Comparative)
By Lexi Zimmerman
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(Mst in Sustainability Leadership from Cambridge University)
Say Hello
I am very interested in exploring how technology can make academic research more accessible and collaborative. If you have feedback on the website or think there may be an opportunity for further collaboration, please use the form at right.
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Reflect: To ground my research I first completed a literature review of the apparel industry focusing on the system dynamics of fast fashion and industry initiatives. I also compared the KFIs with the indicators for the Sustainable Development Goals, Global Reporting Initiative, B Corporations, and the Material Circularity Index. While I was writing my literature review it was available for public comment as a google doc.
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Act: I created this website in an effort to explore how research can be made more accessible for practitioners. Next, I sought to apply the Future Fitness indicators within the context of Apparel Supply Chains. This required building out a landscape model to juxtapose the two concepts.
Collect/ Analyze data: Next I populated the landscape model with data from public reports available online from Patagonia, PVH, and Gap. The individual company raw data can be reviewed under deliverables
Reflect: The data shows, somewhat expectedly, that industry-wide initiatives are more robust than the future fitness guidance. For example, the "employee health is safeguarded" KFI is not nearly as detailed and in depth as the HIGG or FLA framework with their code of conduct and thousands of individual findings. There were also several intersections of the KFI/ supply chain model that had no data across any of the companies analyzed. (e.g. products emitting no GHGs , customers being informed of harm, and paying the right tax at the right time) Finally, some initiatives don't have a clear place in the future fitness framework; such as, philanthropy or activism.
Methodology
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Engage with the real world situation
I focused my first year of research on investigating these questions:
- How is software currently being used to enable sustainability managers for global apparel companies to measure and manage their supply chains most effectively?
- Can industry level organizations utilize software and anonymous data to bridge the “sector gap” and standardize innovations in supply chain sustainability across the apparel industry?
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My anonymized final research deliverable can be downloaded under Deliverables here
The research question dictated a two phase structure
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Theoretical applicability of KFIs:
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Creation of a supply chain/ KFI model for qualitative data
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Populating the supply chain/ KFI model with public data from Patagonia, PVH, and Gap
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Technical feasibility of KFIs:
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Creation of a database for KFIs for quantitative data
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Populating actual indicators with data from public Corporate Social Responsibility reports available online
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Cycle 1: Create a future-fitness apparel model and populate with data
Cycle 2: Populate indicators with quantitative data
Act: To unpack the distance between the current reality and the future possibility for KFI data, a full database of all of the KFIs and the components necessary to derive them was required. The 21 high-level KFIs actually required 550 distinct data points. An example of this is that to derive the single KFI of “All energy is from renewable sources,” seven independent indicators were required
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Collect/ Anlayze data: The database of indicators is available for download under deliverables
Reflect: I quickly discovered that there is actually very little quantitative data available publicly. Furthermore, where there is data disclosed often times all the components required to calculate future fitness were not given. For example Patagonia says "In FY 2015 we generated 203,502 kWh of on-site renewable energy and purchased 980,112 kWh of green power." This is useful information; however, without the context of the total energy used future fitness can not be calculated. Another example is both Gap and PVH released the total gallons of water used across their supply chains with 314,364,742 gallons and 343,683 gallons respectively. However, to calculate the water KFI, the value of total gallons needs to be further qualified. Specifically, the water needs to be used in an environmentally responsible and socially equitable way and not extracted from water-stressed regions.
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Milestones
Deliverables
I have chosen to utilize Participatory Action Research (PAR). PAR is an approach to research that emphasizes participation and action. It seeks to understand the world by trying to change it collaboratively and following reflection. It emphasizes collective inquiry and iterative experimentation that is grounded in experience.
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In this study, the PAR methodology fit the question, as it lent itself to research cycles, as well as the content because the technology context evolves rapidly. It also fit my natural inclination toward reflection and evolving research. I believe action research will become more important as we move forward into an increasingly unpredictable future.
