Sustainability Reporting Analysis: Quorn

Project Objectives and Focus

In Quorn’s 2019 sustainability report, plans to develop a ten-year roadmap that includes specific relevant targets were identified as next steps for environmental issues. Many of Quorn’s carbon emission claims are currently focused around comparisons to the meat industry, and the water goals are currently limited to a single metric, water use per ton of production. As a plant-based meat alternatives company, highlighting the environmental impacts when compared to meat is important for consumers looking to shift their eating habits. However, a useful and effective sustainability report will utilize measures that will also allow investors and interested stakeholders to analyze Quorn’s environmental impacts to other companies within their own industry.

This report will focus specifically on the water goals that Quorn should be implementing in their next ten-year planning cycle. These goals will be identified through data analysis and comparisons will be targeted to the agriculture industry wherever possible to ensure that Quorn’s plant-based food production is compared intra-industry. The latest sustainability report also mentioned that one of the three large factories is in a drought-stricken area which indicates a need for solution ideas that can help mitigate those risks as well (Quorn 2020, 22). Since Quorn’s production facilities reside within the United Kingdom, datasets will be utilized to understand the trends and projections for future water resources for the UK specifically. The analysis of these diverse datasets will lead to the development of science-based targets for water use and clarity around how Quorn should manage the water-related aspects of their business model to ensure the company can continue operations and continue to deliver value in the long term.

Description, Source, Size and Other Pertinent Characteristics of the Dataset Employed

Several datasets and publicly available information were utilized for this report. Two primary datasets have been collected to provide detailed information around trends in water use and water use efficiency. The UK’s Department of Environment and Food & Rural Affairs released a dataset that includes all of the water abstractions from surface and groundwater sources for 2000 to 2017 that is broken out in a variety of industries like agriculture (Department for Environment Food & Rural Affairs 2019). This 2019 dataset consists of water extraction volumes in millions of cubic meters by nine different industries per year in UK and is available in CSV format.

The other primary dataset used to analyze water use efficiency trends comes from the Food and Agriculture Organization of the United Nations. This dataset consists of approximately 44,000 different pieces of information that comprises a collection of global water use efficiency data from 269 different countries for the years 2000 to 2017. The primary metric within the dataset is gross domestic product (GDP) in US Dollars per cubic meter of water used and is the metric used as the direct indicator of the Sustainable Development Goal (SDG) 6.4.1: change in water use efficiency over time (Food and Agriculture Organization of the United Nations 2020). The specific data for the UK is only available for 2005 through 2017 so that will be the timeframe of focus for that dataset. These two datasets will inform not only the absolute water volumes Quorn should be basing their water goals upon, but will also provide information on water use efficiency that directly tie to the SDGs.

In addition to the two primary datasets, the UK government’s reporting on future water scarcity projections will also be referenced to provide more context to the historic datasets analyzed. Data was also obtained around the water required per ton of vegetables, as well as chicken, pork, and beef products, to highlight how Quorn’s sustainability reporting should focus on industry specific metrics to be more useful for investors and other stakeholders looking to compare their business practices to other plant-based food production companies.

Research Questions for the Initial Analysis

The exploration of public water datasets will be utilized to determine what annual water usage targets would support sustainable water extraction. Water extraction information will then also be paired with the water use efficiency information to determine if Quorn’s current goal of 25% water use efficiency improvement is an aggressive enough goal compared to historic trends. Once the questions of what sustainable water extraction levels are, and what water use efficiency goals would support those levels, the question of how the organization should manage the water-related aspects of its business model will be addressed. These primary questions will allow Quorn to develop an aggressive set of targets to manage their water consumption and ensure they are setting goals that allow them to be a more resilient organization that can continue to deliver value in the long-term.

Analysis Techniques Employed

To begin the analysis, data from the water use intensities of the meat industry versus vegetables was analyzed. A comparison was determined by visualizing three separate meat products, chicken, pig, and bovine, against vegetables. The average water use intensity from the different meats was then averaged to get a single average water use intensity value for meat. The water use intensity of vegetables was then compared to that figure to determine how many tons of vegetables could be grown with an equivalent water amount. This comparison helps support the suggestion that Quorn should be focusing on their own agricultural industry to ensure they are making valuable comparisons.

The second part of the analysis focused on analyzing the water abstraction data for the United Kingdom and specifically the UK agricultural industry. Data from 2000-2017 was available for analysis and was used to determine the rate of change over time. The rate of change was calculated as a percentage to indicate the current pace of reductions in the industry, as well as the rate for the country. This analysis helps provide historic context on the rates of change in water extraction over time so it can be compared to Quorn’s current goals to determine whether they are aggressive enough.

The water use efficiency dataset that was available was not broken down by industry, however, it did have useful distinctions by country, so the United Kingdom was able to be isolated from the global figures as well. For this dataset, like the water abstraction data, a rate of change over time analysis was performed to determine how water use efficiency has been changing overtime. These results were then compared with the absolute water abstraction rate of change to determine if there is a water use goal that can be informed by both approaches.

Insights Obtained

Through the analysis of these different datasets, a variety of insights were collected to help inform how Quorn should develop the next set of ten-year water use targets that are science-based. The first insight developed confirms that Quorn should be focusing sustainability report metrics around not only the SDG water use intensity metric, but also when utilizing comparisons to other organizations, should be focused on the agricultural industry. As seen in Figure 1 below, the agricultural industry differs greatly from the livestock industry. Nearly 27 tons of vegetables can be grown with the same water as 1 ton of meat. This indicates that the use of the livestock industry as a comparison does not provide valuable information for a stakeholder looking to understand Quorn’s footprint in relation to other plant-based alternatives. Shifting to more industry comparisons will provide investors and stakeholders greater transparency in understanding Quorn’s business processes that can enable improved market reputation and brand identity. While not recommended to use within the sustainability report, marketing materials focused on the impact members of society can make by shifting their eating habits can still be a useful way to identify the environmental impacts of supporting the Quorn brand.

Analyzing the agricultural industry within the UK specifically provides greater indication of water use trends. In Figure 2, the water abstractions from the agriculture industry can be seen over the years 2000-2017. The reduction during that period equated to approximately 61%, with an average rate of change of a 3.6% annual reduction. When compared with Quorn’s current goal of a 25% reduction, the current goals fall short of the current long-term trends. This indicates that Quorn should be more aggressive in goal setting as plans to set a new ten-year goal are determined to keep pace with the market. A large long-term goal can then be broken down into an annualized goal to ensure progress to the target is being met. The reduction of water abstractions not only reduces business costs, but it helps reduce the organizations impact on the local environment. This helps increase brand reputation while avoiding potential risks from environmental regulations that are continually tightening and focused on the largest contributors to the issue.

Total water extraction goals are important, but as an organization grows, often the need for resources becomes larger with each additional unit of product produced. For this reason, the SDG 6.4.1, change in water use efficiency over time, is the suggested metric to be able to analyze the efficiency of water use over time so an organization can be compared with other organizations within an industry that may be at different sizes as well. The water use efficiency data available does not break out water use efficiency by industry, however, it does still provide insight into the rate of change that water use efficiency has impacted gross domestic product over time. Globally, and in the UK, water use efficiencies measured in GDP has increased between 2005 and 2017. A similar trend can be seen in Figure 3 where the change over time historically has been much larger than Quorn has established for their current water goals. Implementing stronger water use efficiency goals will allow Quorn to keep up with their industry, country, and globe as the focus on reduced water resources continues to increase.

Over that 12-year period, GDP water use efficiency has increased by 42%, or 3.5% annually, for the UK. Across the globe an even more aggressive 75%, or 6.3%, has taken place. This data indicates that Quorn should be setting aggressive water use efficiency goals so business processes can continue to scale in a resource constrained future. Water use efficiency goals will help Quorn to achieve the total water abstraction goals, but will also allow for greater value to be derived from their products by reducing the costs from water and reducing the risks from the projections of water resource constraints that are expected for the future where nearly 33% more water is expected to be needed  (National Infrastructure Commission 2018, 4). These expectations of increased water constraints indicate the need to proactively manage the businesses risk regarding water. The organization should not only develop strong sustainability targets for water-use but should also ensure the material nature of water resources are understood through the organization by providing education, incentives, and investment in water efficiency improvements within all elements of the business model.

Recommendations for Further Research

Data availability for water use and efficiency is still limited. As data becomes available, further details around the agricultural industry’s specific water use efficiency would be useful in understanding how the industry is specifically making progress in that SDG metric. Specific water abstraction information by county in the United Kingdom would also be useful in understanding the volume and trends of water resources within the specific locations of Quorn’s largest processing plants. As data prediction analysis advances, improved water scarcity projections that are granular to county would also improve understanding of the future water scenarios instead of focusing primarily on historic analysis to guide goal setting. To support aggressive water reduction goals, a variety of supporting actions should be undertaken to support achievement of the targets. Education, incentives, and investments directly focused on water use efficiency should also be measured, so further research on effective targets for those supporting elements would be helpful in ensuring the organization is not only setting strong goals, but also achieving them through strategic planning.


Quorn’s identification of the need to develop science-based targets for their water usage goals is an important first step to improving the initial goal of a 25% water use efficiency reduction. Based on analysis of the available datasets, Quorn should be setting goals above 33% to match projections of future water needs and based on trends in the agriculture industry should be setting those goals around 50-66%. With a water use efficiency goal of a 5-7% average annual reduction, Quorn can continue to improve their brand reputation with the public and investors while reducing costs and risk from tightening regulations by having strong goals that showcase leadership in this environmental topic. These aggressive targets should be paired with organizational support through education, incentives, and investment to ensure that business operations have the tools necessary to achieve these goals. As water resources continue to rise in importance globally, setting aggressive targets that are supported with organizational action will be critical to ensure continued value creation in the long term for investors and society through improved business processes. Quorn’s adoption of more aggressive goals will allow it to be more resilient to future water scarcity and will improve their market reputation and brand identity for long term business success.

Author: Logan Callen


Department for Environment Food & Rural Affairs. 2019. “Estimated Licensed and Actual Abstractions from All Surface and Groundwater Sources by Purpose: 2000 to 2017.” Accessed February 21, 2021.

Food and Agriculture Organization of the United Nations. 2020. “Indicator 6.4.1 – Change in Water Use Efficiency Over Time.” Accessed February 21, 2021.

Global Reporting Initiative. 2018. “GRI 303: Water and Effluents 2018.” Accessed February 09, 2021.

Mekonnen, M.M., and A.Y. Hoekstra. 2010. The Green, Blue and Grey Water Footprint of Farm Animals and Animal Products. Value of Water Research Report Series No.48, UNESCO Institute for Water Education.

National Infrastructure Commission. 2018. “Preparing For A Drier Future.” Accessed February 21, 2021.

OECD. 2013. “Water and Climate Change Adaptation: Policies to Navigate Uncharted Waters.” Accessed February 09, 2021.

Quorn. 2020. “Quorn – Healthy Protein For People and Planet: Sustainable Development Report 2019.” Accessed February 02, 2021.

United Nations. 2015. The 17 Goals. Accessed February 10, 2021.

Winston, Andrew S. 2014. The Big Pivot: Radically Practical Strategies for a Hotter, Scarcer, and More Open World. Boston, MA: Harvard Business Review Press.

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