Revolutionizing Corporate Impact Assessment: A New Approach
Assessing corporate impact has always been a challenge for investors, employees, and customers. The scarcity of trustworthy and comparable data has hindered the ability to evaluate the true net impact of companies. Having worked at UN PRI, I understand these challenges firsthand, which led me to the groundbreaking work of the Upright Project, a Finnish impact data company.
The CFA Institute Research and Policy Center highlights the uphill battle faced by stakeholders due to inconsistent and unreliable data when it comes to understanding the financial risks and opportunities arising from climate change. However, the Upright Project aims to change the game with its unique approach to impact data modeling.
Upright’s net impact model goes beyond traditional methods by classifying over 150,000 products and services and leveraging more than 250 million academic articles to determine the science-based impact of each. This data is not just comprehensive but also publicly accessible, with profiles of over 10,000 companies available for free on the platform.
Unfolding Applications of Upright’s Data
As an advocate for applying scientific evidence to real-world scenarios, I am excited to explore the potential applications of Upright’s data. Private equity, venture capital investors, asset managers, and asset owners are already benefiting from the transparency and objectivity of the model, using it for risk assessment and stewardship.
Challenges and Opportunities of Granular Data
The granular nature of Upright’s data allows for detailed insights into a company’s impacts. By examining specific business units and impact categories, investors can make informed decisions about their portfolios. The platform’s unique approach enables comparisons across different asset classes, offering a holistic view of a company’s impact.
Utilizing Upright’s Platform for Impact Evaluation
To demonstrate the practicality of Upright’s approach, let’s take the example of Siemens. By using the platform, investors can assess Siemens’ business model, impact categories, and product-specific impacts to gain a comprehensive understanding of the company’s net impact.
With Upright’s Bayesian inference machine learning model, investors can uncover causal relationships between products and positive or negative material outcomes. This data-driven approach revolutionizes the way companies are evaluated, providing a new lens for investors to make informed decisions.
As we continue to explore the possibilities of Upright’s data model, the future of corporate impact assessment looks promising. By leveraging scientific evidence and innovative modeling techniques, we can move towards a more transparent and sustainable investment landscape.