Developing Enterprise Water Targets Informed by Local Contexts: Cargill’s Approach

Companies rely on clean water supplies that are increasingly threatened by growing populations and demand, climate change, and inadequate governance. Traditionally, corporate water stewardship has narrowly focused on mitigating water risks to direct operations. Recognizing that water dependencies and impacts can occur anywhere across a value chain, water stewardship activities are evolving into more comprehensive and contextualized strategies that are inclusive of upstream and downstream business activities and locations.

Many companies are assessing water risks to their operations and recognizing that their dependencies and impacts on water can occur outside of their direct operations. They are responding by setting enterprise-wide contextual water targets that reflect water challenges in priority locations across their value chains. Setting enterprise-wide water targets informed by the catchment context helps companies address water-related risks, increases business resilience, and helps solve water challenges in the places that matter most across their value chains.

The purpose of this Practice Note is to share a case study of one such approach to setting contextual water targets, developed by WRI and Cargill, one of the largest privately held food, feed, and bio-industrial companies in the world. WRI followed three steps to determine enterprise-wide contextual water targets for Cargill: (1) assessing water impacts and dependencies across the value chain and prioritizing the most important activities; (2) assessing water-related risks and prioritizing locations; and (3) setting targets for priority locations that are proportional to the company’s contribution to the water challenges.

The guidance serves as a high-level framework with substantial flexibility in how each step is implemented. We hope to provide other companies with an example to learn from and a deeper understanding of the importance of enterprise-wide contextual water targets.

Key Findings

WRI followed three steps to determine enterprise-wide contextual water targets for Cargill:

Step 1: assess and prioritize sections of the value chain that have the most important dependencies or impacts on water resources.

Cargill and WRI prioritized two sections of the company’s global value chain: the upstream agricultural crop supply chain and direct operations. Cargill’s upstream supply chain of agricultural (i.e., crop) production was identified as the most essential section of the value chain, given that agriculture relies heavily on — and can negatively impact — water resources. Because Cargill has more control over direct operations, these were also prioritized. These two sections of the value chain represent where Cargill has the largest footprints and the greatest ability to drive change.

Step 2: assess water-related risks and prioritize locations within the sections of the value chain identified in Step 1.

WRI and Cargill assessed risks most important to Cargill’s business and to people and agriculture: water availability, water quality, and access to water. Using WRI’s Aqueduct suite of tools, we assessed global indicators for these water risks for each catchment in which Cargill operates or from which Cargill sources agricultural crops. Catchments were prioritized for the severity of the water challenge. We also determined materiality thresholds, such as the proportional share of water consumption attributable to Cargill’s agricultural supply chains in the catchments, to prioritize action based on Cargill’s value chain footprint. Catchments exceeding both thresholds were prioritized for target-setting.

Step 3: set targets for the sections of the value chain identified in Step 1 and for the water challenges and locations identified in Step 2.

Well-crafted enterprise water targets should drive action at the local level that is at least proportional to the severity of the water challenge and the company’s contribution to that challenge. In response to factors such as data availability and direct control, Cargill set a combination of outcome- and process-oriented targets for each of its priority catchments and facilities.

In total, Cargill committed to restore 600 billion liters of water.

• Cargill also committed to reducing five million kilograms of water pollutants, improve access to safe drinking water, and implement water stewardship programs to meet desired conditions for waterbodies in priority watersheds.
• WRI and Cargill remain open to recommendations for improvement and hope the approaches taken illustrate gaps in data and thought leadership. Furthermore, we recommend reviewing and updating the target setting methodology every three to five years, as data and guidance are rapidly evolving.

As one of the first companies to set contextual water targets at an enterprise scale, Cargill’s experience offers valuable lessons.

• A company’s largest footprint — and greatest source of risk — may be outside of their direct operations. This is particularly true for sectors heavily reliant on agriculture, like food, beverages, and textiles, or sectors where the product use relies on water. Assessing impacts and dependencies across the entire value chain is critical to ascertain the most important sections on which to focus.
• Pragmatism is critical in the absence of plentiful data. To set robust contextual water targets, ideally one would have full transparency across the value chain and access to current monitoring data and site-specific models. In reality, data gaps may be plentiful, and resources do not allow for site-specific assessments across global enterprises and their value chains. Applying global models and datasets like Aqueduct can facilitate an efficient and scalable method across large portfolios using the best available globally comparable data.
• Pioneering strategies require humility and should be adaptively managed. For example, without clear standards for desired conditions on a global scale, these early approaches to setting meaningful water targets across enterprises rely on best available data and professional judgment.