Challenge: insufficient impact data
Finally, some companies may either not yet have — nor be able to collect — data that demonstrates their wider social or economic impact. In the first situation, many companies are typically accustomed to reporting ESG metrics that show the effects of their operations (how they function) rather than the impact of their products and services (what they produce). In the second situation, some companies’ ultimate impact is difficult to measure; for example, positive community health outcomes or reduced societal inequality.
Potential approach: Work with information that a company may already track to ensure a reliable, repeatable data series, and engage to improve impact data collection and availability. Our company engagements typically include open dialogue about best practices for impact reporting. Emphasize an impact logic chain that establishes a tangible link between a company’s activities and outputs to actual impact. Find a credible evidence base that links an available KPI to the ultimate societal or environmental impact. For example, a generic-drug manufacturer enables access to lower-cost drugs, the ultimate impact of which is broader access to health care. This is very difficult to measure, especially across a company’s entire product portfolio. Focusing on the company’s output — the volume of generic drugs and their prices, relative to brand-name versions — is more practical. From here, an investor can derive a KPI that tracks anticipated cost savings for customers and use this as a proxy for increased access to treatment.
Final thoughts: Overall, the impact community will need to find ways to balance subjectivity and nuance with objectivity in assessing and measuring impact. We should establish a strong evidence base when including companies or issuers in an opportunity set. We will need solve for indirect impact, and work to minimise and track the reduction of negative impact. Finally, impact practitioners should establish intentional and productive courses of action when available data fails to adequately demonstrate impact, bearing in mind that the point of IMM is not only to improve measurement, but also to maximise real-world positive social and environmental outcomes.