One of the new mental torments in corporate finance relates to so-called ‘Scope 3’ (S3) emissions, i.e., greenhouse gases (GHG) indirectly emitted by a firm along its supply chain. These emissions are beyond a firm’s immediate control. They feel distant and abstract.
And they are notoriously difficult to measure. In a 2022 report, the academic authors criticize firms and ESG data providers for severe inconsistencies across S3 data sets available to investors. I sympathize with those who are frustrated with this new metric.
This is where J. Rotter’s contribution to social learning theory (1966) comes into play. Mr. Rotter, who was a psychologist, defined ‘locus of control’ as the degree to which individuals believe they have control over the outcomes in their life. Those with an internal locus of control tend to see life as a result of their own actions; those with an external locus of control attribute the outcomes to external factors.
Regulators are incentivizing firms to internalize the locus of control, i.e., to own their destiny and share responsibility for value chain emissions. They rely on robust arguments.
Typically, S3 emissions represent three times the combined Scope 1-2 (S1-2) emissions.* The S3 intensity for the average firm is c.800 million tons,** a benchmark when evaluating any asset. The 80/20 rule applies: on average, of the fifteen S3 categories, two of them, purchased goods & services (upstream) and the use of sold products (downstream), account for 30% and 40% of total S3 emissions, respectively.
Investors must, therefore, be enabled to account for different S3 intensities amongst industry peers in a given sector. The ones producing more S3 emissions incur a greater risk of being squeezed between more expensive suppliers and less profitable customers in a tightened regulatory environment (e.g., CO2 tax).
From another angle, it would be mistaken to assume that a company with less vertically integrated operations than a direct competitor (components, assembly) and thus generating less S1-2 emissions faces materially different risks and opportunities from a GHG emissions perspective.
The GHG protocol lists many initiatives to reduce S3 emissions as a matter of risk management. They include engagement and co-creation with suppliers and customers, as described in ‘The Multi-Staged Engagement Rocket’ (2022). In this context, S1-2 emission intensity is essential, independently of its magnitude. A company will more effectively engage with value chain partners if it sets an example itself.
As a side note, while the concept of scope 4 (avoided) emissions can be valuable to market a decarbonization strategy, it can be complex and confusing. Offsetting S3 with Scope 4 emissions is discouraged since it creates a meatball burger.
In sum, dealing with S3 data is a headache, and committing to related targets can add nausea. Under these circumstances, transparency about methodology and data quality is essential. Whether one likes it or not, if a firm does not own the disclosure of its S3 emissions and does not include them in its equity positioning, data providers and investors will come up with their own story.