Corporate impact measurement is a daunting task that requires valuable time and significant resources. Having experienced the challenges faced by investors, employees, and customers firsthand, I have witnessed the struggle to access credible and comparable data to evaluate the overall impact of companies.
The CFA Institute Research and Policy Center’s report on Climate Data in the Investment Process highlights the hurdles stakeholders encounter due to inconsistent and unreliable data. This poses a challenge for investment professionals aiming to manage financial risks and opportunities arising from climate change.
Joining the Upright Project, a Finnish impact data company, shifted my perspective on data modeling. Embracing an approach that organizes scientific evidence systematically, Upright has created a unique dataset that allows for global company comparisons from an external viewpoint.
- Upright’s net impact model sorts over 150,000 products and services, aiding in defining the business models of every company in its database.
- By leveraging more than 250 million academic articles, the model determines the science-based impact of each product and service.
- This aggregated data at the firm and portfolio levels helps quantify the total material impact of an investment, with over 10,000 company impact data profiles publicly accessible on their platform.
Inspired by this innovative solution, I was motivated by the fusion of scientific evidence and practical applications for investment practitioners and investors.
Applications Are Unfolding
Enhancing the learning process through investor feedback, the potential applications of this data remain unfolding. While private equity and venture capital investors have been early adopters due to the model’s outside-in approach, asset managers and owners also find value in its transparency and objectivity for disclosure requirements.
Granular Data: The Challenges and Opportunities
The granular nature of the data provides investors the means to identify specific business units driving both financial and non-financial impacts, offering opportunities for risk assessment and stewardship. This model’s applicability to both private and public companies allows for cross-asset class comparisons, aiding in isolating exposure to particular impact categories.
The platform’s potential for evaluating a company’s impact involves several steps:
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Assessing the business model based on a products- and services-based approach
- Using Siemens as an example, analyzing their product mix and revenue on the platform reveals key insights into their operations.
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Selecting an impact category of interest from the four main categories
- Health, environment, knowledge, and society make up the core impact categories. Understanding Siemens’ impact within these categories is crucial.
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Determining upstream, internal, or downstream impact
- Pinpointing where the impact occurs along the value chain within a company’s operations provides a comprehensive assessment of their influence.
- Analyzing products and services associated with the chosen impact category
- Identifying which offerings contribute most to both positive and negative impacts offers a holistic view of a company’s influence.
Employing a Bayesian inference machine learning model, Upright draws from millions of scientific articles to discern the causal relationships between products and services sold by companies. These insights allow investors to grasp the full impact their companies and portfolios have on society and the environment.
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