However, current ESG measurements lack transparency and are mostly about the internal costs as well as impacts of company operations. To achieve societies’ goal of ecological sustainability and social justice, which is the dream of stakeholder capitalism, new metrics of ESG must be developed that involve consumers in order to help them to collaborate with ESG goals, as well as “external ESG” metrics that measure the impact of companies on the communities in which they operate.
The area of ESG metrics for consumers already has some quite successful examples that hopefully will show the way for others. Since travel and home energy are typically the two biggest categories of consumer energy use, companies have had the greatest motivation to address these two particular commercial cases. Below, a few examples are provided.
Ant Forest (owned by Alibaba) is a mobile phone app that plants trees in deforested areas if users take a step toward reducing their travel-related emissions, or by going paperless, or buying sustainable products. Ant Forest is nearing a billion users, and has planted millions of trees, and demonstrated an 8.6% reduction in users’ travel-related CO2.
OPower (owned by Oracle) measures home energy use, and provides homeowners with feedback on their energy use. This feedback, without additional incentives, achieves a 3-5% reduction in home energy use in homes across the USA.
The impact-tech startup scene has been thriving for several years already. Doconcomy (a Swedish impact-tech start up) provides consumers with insights on how their transactional activity impacts the environment in terms of CO2 footprint (Åland Index), and it also recommends actions on how to modify their consumption behavior. With the increasing maturity of the open banking solutions, banks and other payment solution providers will need to act quickly and align their services to the emerging customer values.
In addition to involving consumers in ESG goals, it is important to measure the impact of a company on the communities in which it operates. The UN’s Sustainable Development Goals (SDGs) includes ESG-type metrics for measuring the environmental, social, and governance of communities (which one of the current authors helped create). Census departments are beginning to generate these statistics to help governments and international aid agencies better focus their efforts on achieving the sustainable development goals.
However, the SDG metrics do not measure the impact of particular companies’ operations on the communities in which they operate. Development of “external ESG” metrics that relate company operations to community well-being and sustainability is a critical but so far neglected part of measuring company ESG. Interestingly, the sorts of methods used by OPower to measure home-by-home energy use (such as statistical analysis and pattern recognition of utility energy data combined with 3rd party data) may be the path for developing external-facing ESG measurements. As these external ESG metrics are developed, they can help companies and investors be better citizens among the communities that they operate in.
To achieve the goal of more sustainable economic activities and projects, it is critical to have the right ESG data and to employ this data in a transparent and accountable manner. By developing the right sorts of ESG metrics and usage parameters, we can make the world a far better place for ourselves and future generations.
Alex Pentland
MIT Professor Alex Pentland leads the MIT Connection Science program, and previously co-created the MIT Media Lab. He is a pioneer in the field of computational social science and a leader in data privacy. He has served on boards of the UN, Google, AT&T, and is a member of the US National Academies.
Julinda Gllavata
Julinda Gllavata has been with SIX for more than seven years. In her current role, she leads the Banking Services data science team. Prior to joining SIX, Julinda worked for different international companies such as Accenture, Bosch, and OMRON.
Her educational path led her from Albania to Germany to start her PhD studies in Computer Science in 2000. Her dissertation focused on the application of machine learning techniques in image processing and pattern recognition.