What does it take to create a new bottom line?

If we want investors to elevate social and environmental returns to the same level as financial returns, we first need to arm them with a metric that demonstrates what exactly success looks like.

Util was founded on a simple assumption: if there existed a unit that accurately captured the way in which a company affects the world around it, investors could maximise not just their financial but also their social and environmental returns on investment. 

In short, we could create a new bottom line for investors.

All decisions in the investment world—be it a pension scheme choosing a fund manager or a fund manager selecting companies for a portfolio—hinge on relative financial performance. Asset owners seek asset managers that have outperformed a benchmark. Fund managers select companies that are likely to be more profitable than their peers. All other considerations are evaluated in terms of how they support (or undercut) relative financial performance. Did reweighting my portfolio increase my financial returns? Did launching a new product make us more profitable? Did changing our supply chain improve our unit economics? 

Sustainability is no exception. Asset managers advertise their sustainability credentials to attract clients. Fund managers incorporate environmental, social and governance (ESG) data into investment processes to increase risk-adjusted returns. Employees hit sustainability criteria when doing so is linked to financial incentives.

It’s no surprise, then, that existing providers of sustainability data market themselves as a resource to enable alpha, reduce beta, or increase flows. When sustainability data does lead to positive outcomes for stakeholders—for example, an investor mandates that a company reduce its carbon emissions or decrease its gender pay gap—this is viewed as a positive, but tangential, footnote. Financial gains are still the end goal. 

Within this singularly focused framework, how do we elevate social and environmental outcomes, or non-financial performance, to the same level as financial performance? 

Perhaps the best solution is to replicate the playbook. 

Capturing financial performance is easy because it can be measured with a single metric: currency (internationally recognised as the dollar). There are four reasons why the dollar works as a decision-making superpower.

First, it’s comparable. You can compare how many dollars you made from an investment with how many dollars someone else has made. It’s also fungible, meaning you can compare the financial success of investing in, say, cocoa, with that of investing in blue-chip US equities. As a result, it’s possible to make money from one asset and invest it in another.

Second, it’s aggregatable and sophisticated. You can not only compare Apple’s earnings with Amazon’s but also compare the unit cost of each of the iPhone’s individual components or the average margin on every book sold by Amazon. That makes it possible to build a thesis based on top-level relative performance and evidence it with the numbers underpinning the top-level results. 

Third, it’s automated. Financial results are automatically available to financial decision-makers—and at low cost. For a few thousand dollars, investors have access to a wealth of comparable financial information that allows them to make evidenced investment decisions. The low cost encourages more use and so even more comparability. 

Finally, dollars are both tangible and trusted. Generally Accepted Accounting Principles, along with the money deposited into bank accounts, help to ensure we trust the dollar and so can make comparative spending decisions without worry that the numbers we see in front of us might be wrong. 

Having a comparable, sophisticated, automated and universal metric like the dollar makes financial decision making possible. Why shouldn’t it also work for non-financial decision making? 

That’s the challenge we’re trying to crack at Util. 

Our analytics are comparable and, to an extent, fungible. Our metric—a Util—for company and fund impact is comparable against peers, against a benchmark and against time. And because non-financial data covers a wide range of virtues, it’s also comparable across different social and environmental impact areas. Did Facebook have a greater impact on mental health last year than Apple did on primary school education? Are oil refineries as bad for the climate as tobacco is for healthcare? Although the market cannot yet store Utils, the fact they’re comparable and fungible makes our analytics valuable for investors trying to make truly informed decisions.

They’re also both aggregatable and sophisticated. We look at the impact margin of an entire fund as an aggregation of its holdings in the same way that we look at the impact of an entire company as the sum of its individual products. What’s more, although the Util is a single impact unit, we can also break impact down into themes—healthcare, climate, poverty, equality etc.—to add an extra layer of depth.

Our analytics are automated. We use machine learning to automate the process of gathering and analysing vast amounts of data, synthesising it into a single, comparable metric. That lowers  cost and friction, increasing usability and so comparability. 

Finally, our analytics are transparent. As a result, they have a greater chance of being universally trusted and relied upon. We publish our methodology to users and provide sum-of-the-parts data to provide a holistic picture of a company’s impact.

Our vision is a world in which all capital allocation maximises both financial and non-financial returns. If we’re to replicate the success of financial investing, however—where financial comparability is key—we need to arm investors with the tools to make truly informed decisions. 

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