Big League: Transforming the capital markets with impact rigor and disclosure



I recently opened my ImpactAlpha daily brief and read, “Swiss Re to move $130 billion portfolio to track ESG indexes.” That was followed by, “World’s largest pension fund hits responsible investing milestone.” Then, “New Mexico commits $50 million each to TPG Rise and BlackRock Renewables funds,” which led to, “Institutional investors oversubscribe BlackRock renewables fund.”

Wow. It seems like yesterday that impact investing was, for the capital markets, somewhere between a sideshow for the Birkenstock-shod wealthy and a “place to dump the dogs,” as one candid Wall-Streeter put it to me in a private conversation.

Things have changed. Mainstream entrants now dominate in impact assets under management. Early movers who weathered years of slow growth, marginalization, and even derision now face a new set of problems: rapid growth, acceptance, and, gulp, market-driven performance expectations.

We used to try to coax people into the pool by saying, “Come on in, the water’s fine.” Now, immense players are doing cannonballs off the high dive, and there’s no lifeguard. No wonder our fellow early-movers are nervous!

Enterprise-level data

Many have expressed a desire for traffic rules, lane markers and turn signals, as Fran Seegull, executive director of the U.S. Impact Investing Alliance, called for in a recent piece, also on ImpactAlpha. But rule-making is proving nettlesome. For some, the only real impact investing is intentional, and contra-market, or uncorrelated. For others, it’s simply rigorous investor exploration of the mounting social and environmental risks that companies face.

As far as I can tell, the market can encompass these (and other) versions of impact investment with integrity if we build segmented, enterprise-level data infrastructure that supports disclosure, rigor, and transparency across the marketplace.

But impact investing culture, it appears, may be eating its own strategy for breakfast (or less decorously, our young!) While we donors — including foundations and individuals — have been instrumental to the development and growth of the field, we need to let go so our progeny can scale.

Those with strong roots in philanthropy and charitable giving typically exhibit the greatest orthodoxy. Doctrines such as “additionality” (is my dollar making the difference?), “attribution” (will I be able to measure the impact of my investment dollars?), and “intentionality” (do managers and investors intend to make a positive social impact?) seem to be a non-negotiable threshold for labeling impact investments for some.

These practices undermine both capital access and scale without improving data integrity. Their focus on the needs of the individual philanthropic investor mean that small social enterprises (regardless of tax status) are routinely undercapitalized and creak under weighty bespoke metrics and naïve scaling expectations.

At the other end of the spectrum, public company managers scratch their heads over (or dismiss entirely) a flurry of highly customized data requests from investors, Some in both camps simply report on intentions, commitments, and policies, not performance. Worse yet, much of the data is non-standard, non-auditable, and unreliable, making these approaches ineffective as measurement tools.

We need to “true up” impact reporting with conventional data practices across the market. This is not to do away with real differences and nuance in various kinds of economic activity, but to avoid circumscribing the sector into irrelevance. We can honor some the “traffic lanes” Seagull so rightly recommends, and therefore accommodate peers and allies not typically in impact investing’s roped-off area.

Common ground

The principles offered below are intended to outline some of those traffic lanes for a broader impact investing highway. They derive from the Heron Foundation’s experience trying to manage a diverse portfolio in alignment with our mission. We look for common ground across asset classes and tax statuses, and try to measure the overall effect that enterprises have. Embodied in this highly provisional approach is a philosophy that assumes interconnection and interactivity, a varied weighting of impact based on size and similar enterprise characteristics, and recognition of collective impact, which is outside any one enterprise’s “zone of control.”

We are offering this measurement framework in concert with the developing and existing, rapidly improving, and increasingly rigorous off-the-shelf measurement tools now available or under development.

Collect and report data at the enterprise level first. Foundations and donors segment the market by program on the mission side: “rural poverty,” “early childhood,” “employment,” etc. and by asset class on the investment side. But “programs” and causes are mystifying to financial markets. Artificially separating impact from finance by isolating programs from enterprise performance robs them of a realistic understanding of impact investing performance and promise. Looking only at asset classes on the investment side similarly obscures the impact performance of the enterprises that underlie asset classes and give them value.

The current market infrastructure (e.g., Bloomberg, MSCI, GuideStar, etc.) reports data by enterprise (variously referred to as establishment, entity, company, etc.), even though much investor reporting rolls up to the asset class level. This is where the enterprise story is distorted. Enterprises give assets value and are “risk ratable” and “investable,” both financially and socially. Enterprise-level data allow comparisons among every legal form of organization, providing better visibility for investors and managers alike along the mission and financial dimensions that drive high impact.

Segment the market by enterprise on a range of dimensions. Some areas of friction among impact investors — on the role of “intentionality,” for example — can be mitigated by market segmentation based on enterprise size, legal form, industry, geography, and customers. Legal forms such as nonprofits, cooperatives, employee-owned companies, Benefit Corporations, and similar have intention built in. Investors can make choices accordingly.

Over time, longitudinal measurement of comparable peers — whether intentionally mission driven or not — can adjudicate the importance of factors such as intentionality based on performance rather than by culturally-driven beliefs.

Measure negative as well as positive performance. This seems obvious, but literature on impact measurement and donor websites is filled with references to “measuring our success.” If we measure only success, we’re not measuring. Measurement is first and foremost valuable for learning and improving, not for creating an unrealistic marketing wrapper for a specialized group of investors. Excluding negative performance measurement as well as the measurement of unintended negative effects of operations is not only self-defeating in the long run, it is simply dishonest.

From data standards to analysis to ratings. Data are sets of measurements or observations. Standard-setters (such as the Financial Accounting Standards Board) create rules to define data based on consensus about standards. Standards allow analysts and raters start from the same facts. Analysts interpret data, developing a story about the operations, market experience and risk factors of, for example, a particular enterprise. And raters compare a cohort of analyzed organizations to each other, reducing their analysis to a ranking or score.

Ratings that use non-standard data or personal observation are typically opaque, bespoke, non-comparable, and therefore at best incomplete. Any and all of these, when built on the base of high-quality, standard data are very useful.

Report and track data over time. When companies report standard data over time in a peer-comparable format, they produce longitudinal performance information, valuable to managers and investors alike. The resulting analysis can apply to organizations that are similar (or dissimilar) in business model, industry vertical, geography, or any of a variety of “sorts” available. Over time, these analyses build into authentic track records of risk and return, attached to time horizons and contextual factors, which can be factored into improved understanding for both managers and investors.

Use market-wide data standards for the most common factors. While donors are often tempted by personalized metrics and indicators, bespoke data and measurement schemes are expensive, non-comparable, and make “scale” difficult. The market must avoid self-selection of metrics and indicators if we truly want to have peer-comparable data and market impact

As a sector, we could prioritize data points common to all legal forms, (e.g., the definition of “employees”). If we establish “most common factor” data standards across enterprises (and “less common factor” data within industry verticals), segmentation and analysis by cohort will begin to allow informed performance analysis.

Attribute “zones of control.” If enterprises are the unit of observation for measurement, then it follows that data should encompass those things that are in their “zone of control” (i.e., operations, products/services, and the immediate supply chain). For example, direct air pollution from an enterprise’s operations is within its zone of control. “Air quality” in its home state isn’t (even if it intends to improve air quality).

Moving Forward

Invited or not, impact is present and can be positive or negative in large companies and small, in nonprofits and for-profits. All investors need the context of the broader market.

The ideas of “impact investing” and “impact management” encompass a broadening of risk and return analysis for enterprises up and down the economy. They are relevant to managers and investors whether or not they self-identify as impact investors, and they are certainly relevant to a broader public of neighbors, consumers and employees in a smaller and more complex world.

Orthodox impact investors are right to be fiercely protective of the integrity and idealism that has driven the field’s early experience. But cultural provenance has endowed that territory with a set of investment and measurement practices that are contra-market and ill-suited to the vision of capital market transformation that unites the field’s proponents.

Without appropriate enterprise-level data standards, the potential for impact investing to contribute to market integrity for investors, learning for managers, and economic transformation globally will be lost.

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