February 08, 2022 - 1986 views|
To get past a carbon-only approach, businesses need a data strategy that helps them manage information on a range of environmental and social impacts.
In November 2021, I posted a graphic (see below) on LinkedIn that reflects a frequent debate around environmental sustainability: that companies seem overly and narrowly focused on carbon emissions. The graphic was shared more than 1,000 times and reached over 600,000 people. It turns out I’m not the only one concerned about carbon tunnel vision.
There’s no doubt that climate change is among the most pressing challenges for environmental sustainability, resulting in operational risks for organizations. But companies that suffer from carbon tunnel vision ignore the links between the wide spectrum of important environmental and social impacts — like biodiversity loss, land conversion or gender equality. As a result, they risk missing out on important business opportunities and eroding their long-term ability to create value.
We urge businesses to open their eyes to the array of interlinked environmental and social impacts to gain the full breadth of opportunities and value that lie ahead. And the starting point is a data strategy to augment their sustainability strategy — something many companies lack.
Most companies conduct a materiality assessment to identify the most critical sustainability issues to them and their stakeholders. But they often underinvest in building the data foundation to understand their real impact on these issues and effectively manage them.
As a result, businesses make one-off analyses, often by sending spreadsheets back and forth between separate departments or with suppliers. This effort is so labor-intensive that they end up tracking only singular impacts. And because current stakeholder demands for information on carbon emissions are highest, they focus on that.
To reduce overhead and avoid over-indexing on carbon concerns, we advise companies to augment their sustainability strategy with a data strategy that tracks several relevant impacts and provides dashboards customized to different user groups.
Such dashboards should contain the relevant KPIs and methods to measure the most important impacts, and visualize what information would be most necessary for different user groups to act. Whether an energy or procurement manager, each important decision maker should have their own sustainability dashboard to navigate their actions and move the needle on the impacts they influence.
A useful framework for designing the content of this dashboard comes from Doughnut Economics, a visual way of depicting the elements needed for a sustainable and prosperous economy. This includes the ecological factors (in the outer ring of the doughnut) and the social foundations (in the inner ring). (For an idea of what this looks like, click here.)
The “hole” of the doughnut depicts the proportion of people experiencing a shortfall of essential social needs, while the crust of the doughnut represents the planetary “ceiling,” or the point at which environmental resources are overshot and result in ozone layer depletion, air pollution, ocean acidification, etc. The goal is finding the zone in which companies can thrive. If they overshoot or contribute to a shortfall in these environmental and social foundations, then they undermine their long-term ability to create value.
To track their pressure on the ecological ceiling, companies can use Life Cycle Assessment (LCA), which is the most extensive method for assessing multiple environmental impacts associated with all stages of a product’s life, from raw materials to final disposal, including climate change, human toxicity, ecotoxicity, freshwater use or marine and freshwater eutrophication.
To track their shortfalls on the social foundation, businesses can use Social Life Cycle Assessment, a method for analyzing the positive and negative social impacts of a product. It allows companies to track their impact on human rights, working conditions, health and safety, or socioeconomic development on distinct groups of people like workers and employees, local communities or consumers.
Tracking multiple impacts sounds like a big and costly task. But more affordable digital technologies — such as Internet of Things, satellite imaging, data storage or computational power — can radically reduce the cost of data collection and impact assessment. They also help companies cope with increasingly large and complex data volumes available on sustainability issues.
In our experience, a data strategy for sustainability starts with a structured data architecture. To develop it, companies need to develop a point of view on future sustainability data requirements, draft a desired and feasible data architecture, and identify its key use cases. It’s also necessary to identify the technology and software needed, as well as the required investment and expected ROI, for example, on reduced overhead and improved decision-making.
Businesses also need to make the data strategy actionable to help identify interventions that generate co-benefits across material sustainability issues. By linking multiple impacts and addressing them jointly, companies can move the needle on several issues, and avoid unintended consequences of interventions on other impact categories.
Take the example of a large food company that has acknowledged climate change, biodiversity loss and responsible sourcing as some of its most important sustainability issues. The company has realized that these three are highly linked and that regenerative agriculture practices in its supply chain can help drive co-benefits on all three issues.
By investing in regenerative training programs, the company is helping its supplier farms to decarbonize, for example, by building carbon in the soil and through tree crops that store it. Regenerative practices further build biodiversity and water retention in the soil, which can make lands more resilient to heat waves. More resilient lands and richer soils ensure that farmers maintain their ability to earn a living from their farms.
The farmers also reduce their demand for pesticides and fertilizers, which increases their profit margins and positively impacts the company’s responsible sourcing strategy. The company has understood these co-benefits and has decided to invest heavily until 2025 to build regenerative farming practices in its upstream supply chain.
Linking different impacts in interventions requires more variables to track. And collecting new data on these variables can be tedious and costly. A clear data strategy helps manage this increased complexity. It ensures that data collection efforts and technologies are easy to use and integrated in the day-to-day workflows of the people that own the data, and that these people have clear incentives to contribute. The data strategy also needs to adhere to the highest ethical standards to ensure trust, fair practices and data privacy compliance.
Managing this complexity also requires new capabilities for big data analytics. Sustainability managers increasingly need the ability to correlate different variables to understand how they influence each other, and to get new insights on how to steer their interventions for maximized co-benefits and minimized cost.
Moving beyond carbon tunnel vision means taking a more holistic approach to sustainability management. This increases complexity, which can only be managed with more and better information on a range of environmental and social impacts. With the right data strategy, businesses have a powerful starting point for managing and embracing that complexity.