Measuring corporate impact is time- and resource-intensive. Until recently, I worked at A PRI and experienced first-hand the numerous challenges investors, employees and customers face to find trustworthy and comparable data to evaluate the online impact of corporations.
Upright project – a Finnish impact data company – has significantly influenced my perspective on data modelling, and I joined the corporate 4 months ago. Upright’s approach structured all of the scientific evidence in an organised way and created a novel dataset that enabled comparisons of corporations worldwide from an outside-in perspective.
Upright’s net impact model classifies greater than 150,000 services and products. This classification is used to define the business models of all corporations in its database. The model leverages greater than 250 million scientific articles to find out the science-based impact of every product and repair. The data is aggregated at the corporate and portfolio level to quantify the full material impact of an investment. Most notably, a good portion of this data is publicly available: greater than 10,000 company impact data profiles can be found on its platform and subject to a free-to-use policy.
Given my academic background, I used to be inspired by an answer that not only leverages scientific knowledge but additionally offers practical applications for investment practitioners and investors.
Applications are evolving
At Upright, we’ve got learned rather a lot from investors, however the potential applications of this data usually are not yet fully explored. Because the modeling approach is outside-in, private equity and enterprise capital investors have been early adopters of the info. In addition, the model’s transparency and objectivity make it useful for asset managers and asset owners – particularly for disclosure purposes – whether for fund-level requirements or to reveal the general impact of their investments.
Granular data: challenges and opportunities
The full potential of this data will not be yet clear. The granular nature of the info allows investors to pinpoint which business units of an organization have positive or negative financial and non-financial impacts. This creates opportunities for risk assessment and management. In addition, the model’s applicability to each private and public corporations enables comparisons across all asset classes held by an investor. This may help discover high exposures to certain impact categories. Although many investors have sought more detailed information, use cases for this recent, holistic approach to understanding and evaluating corporations usually are not yet well advanced.
Since Upright’s modeling approach is recent to most investors, I’ll illustrate how they will use the platform to judge an organization’s impact.
Step 1: Evaluate an organization’s business model using a product and service-based approach.
Let’s take Siemens for instance. Based on the newest publicly available version of the Upright model, Siemens sells greater than 165 services and products. The company’s total revenue is 77,769 million euros and it employs 320,000 people. About 28% of total revenue is generated from services and products in digital industries, including control devices for electric motors, gas turbines, generators, electric drives, linear motors and more. Details of the complete product mix are visible on the Upright platform.
Siemens’ Digital Industry products
Platform.
Step 2: Choose an impact category that interests you.
The Upright model currently covers 4 fundamental impact categories: society, knowledge, health and environment. Each category has subcategories. For example, under health there are physical illness, mental illness, nutrition, relationships and meaning and pleasure. Impact categories could be each negative and positive. In the case of Siemens, we will see that their services and products have each negative and positive impacts inside the subcategory of physical illness.
The health impact of Siemens
Step 3: Choose whether you might be excited by upstream, internal or downstream impacts.
Products and services don’t exist in isolation. Often, one product is required to make one other, or a user needs to attain an impact using a product. The Upright model has mapped out all services and products so you may assess where in the worth chain the associated impact occurs. In Siemens’ case, 94% of the positive impacts on physical illness or years of life saved related to its services and products occur downstream in the corporate.
Siemens’ impact on the downstream industry
Step 4: Examine the services and products associated along with your chosen impact category.
In the case of Siemens, the services and products that contribute most to the positive impact on physical health are radiotherapy devices, cardiac resynchronization therapy devices, private oncology diagnostic services, ultrasound devices and mammography devices. Taken together, these five products contribute most to Siemens’ positive impact, each because they represent a big share of the corporate’s revenue and since the newest scientific consensus suggests a high positive impact. Causal relationship between these services and products and physical health.
Upright’s Bayesian inference machine learning model finds causal relationships by classifying and translating greater than 250 million scientific articles and other sources. These insights form the idea for determining whether the services and products sold by corporations have negative or positive material impacts, which together provide investors with a comprehensive view of the impact of their corporations and portfolio.
