Finance & Investment

Fair Targets for ESG Performance:
An Introduction

To transform ESG reporting from a feel-good marketing exercise into a forward-looking financial assessment of a corporation’s environmental, social and business risk and an ESG-risk-aware capital-budgeting strategy, ESG targets need to reflect non-market stakeholder needs at a local, regional and global level. We call these kinds of multi-tiered, multi-stakeholder targets ‘fair.’

Brand Provided | By Erik Thomsen | Published 2 years ago | About a 5 minute read

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The need for non-financial reporting

Modern corporations are incredibly powerful; able to produce, in the aggregate, a dazzling array of sophisticated goods and services. But the externalities associated with their activities (i.e., impacts to the environment and human beings as non-market stakeholders) are cannibalizing our natural capital; while the fruits of production are being distributed with less and less fairness.

Non-financial reporting (of which ESG is the latest flavor) has the laudable goal of shining a light on the often-seedy underbelly of a corporation’s externalities in the hope that through transparency will come change. One positive aspect of ESG reporting is the tacit understanding that a company not only acknowledges prior performance problems but also lays out targets for improved future performance. Targets are essential — they indicate where a company is trying to go; the reduction in negative externalities it is trying to achieve.

The problem with ESG reporting

The problem with ESG reporting as currently practiced is threefold.

It is difficult if not impossible to move the needle with self-selected company targets without broader context. Whether we’re talking about land use, freshwater abstraction, toxic pollutants, fishing, employment practices or carbon emissions, corporate targets need to reflect relevant local, regional, industry and/or global conditions. Take water, for example: Just announcing a target for water abstraction (e.g., seeking a 15 percent reduction over the next two years) does not make it the right target. The right target would need to reflect water availability and competing demands — and some goal, stated in real terms that referred to bio-available water. This brings up the second problem.
ESG efforts report on company behavior (e.g., that it abstracted 5 acre-feet of water in a year). But behavior is only one component of impact; the other is the state of the non-market stakeholder (e.g., the watershed, forest, demographic group or the atmosphere) impacted by the behavior. The same behavior will impact different stakeholders (e.g., an arid plain or a flood zone) in different ways (e.g., hurting one and helping the other). Therefore, companies need to report on facility performance, so that it can be combined with local stakeholder constraints (e.g., watersheds) to infer actual and target impacts.
There are no standards to ensure comparability between ESG reports (for either performance or target data). Units of measurement, comparative time frames (e.g., year over year or relative to 2017) and denominators (revenue, earnings, units of output) differ widely between reports, which makes it difficult to combine them for the purposes of aligning the aggregate of corporate targets with sector goals.

As a result of these problems, ESG intentions far outpace ESG results.

ESG reporting needs fair targets

To transform ESG reporting from a feel-good marketing exercise into a forward-looking financial assessment of a corporation’s environmental, social and business risk and an ESG-risk-aware capital-budgeting strategy (which is where the rubber meets the road and change happens), ESG targets need to reflect non-market stakeholder needs at a local, regional and global level and align those needs with the capabilities and behaviors of facilities and their corporate aggregates. We call these kinds of multi-tiered, multi-stakeholder targets ‘fair.’ Fair targets consider the operational realities of facilities, the financial health of the company, local ecosystem and human conditions, the technology substitution possibilities per facility, and the needs of markets local to the facility (e.g., coal-fired power plants may need to continue operating so long as alternatively fueled plants do not exist in the local grid). Emitting less carbon and toxics and consuming less water and land per unit of output is hard; resource-inefficient growth will be curtailed. Fair targets mean the burden is shared equitably.

The process of setting fair targets for ESG behaviors should look similar to corporate budgeting reconciliation, which aligns bottom-up budget requests with top-down resource allocations in an iterative process intended to converge on an optimal set of multi-tiered targets. ESG analysts should be able to query the aggregate of corporate carbon targets by sector (or region) to see if targets are aligned with science-based targets (or the Paris accord). And if they’re not, signals should be sent (e.g., by analysts, investors or governing authorities) to adjust corporate (or sector or regional) targets.

This article series will lay out a general computational framework for establishing practically producible and universally comparable environmental and social targets from widely available third-party data (e.g., CDP and SBTi) and from internal data that all public companies collect (e.g., electric power produced or used per facility) that are fair and actionable (i.e., they can be incorporated into resource-allocation decisions); and which, if followed, will yield the aggregate results we all seem to be looking for (e.g., avoiding environmental calamity by keeping global warming to 1.5°C while fairly sharing any material burdens). The targets can be used to drive the actions of facilities, companies, industries and regions by investors, governing authorities and companies themselves across a wide range of relevant industries and a wide range of spatial and political geographies.

One requirement to being not just a fair but also an actionable target is to have been accurately converted from its source form — namely, that of a real quantity of a real unit (e.g., 25,000 tons of emitted carbon) into its analytical use form; namely, that of a quantity of a financial unit (e.g., a $100 mm increase in costs or a $50 mm reduction in residual asset value) that can be incorporated into business risk assessments and capital budgets and budgeting processes (in the form of probabilistic amounts of some internationally exchanged currency).

The series will begin in the next article with fair carbon targets for the electricity industry — the earth’s largest emitter of greenhouse gases.

Other articles in this series:

Erik Thomsen

Erik is a world authority in the field of multidimensional information systems, an internationally recognized expert in the application of logic to information systems, and a well-known innovator in ontologically grounded approaches to AI and socio-economic-environmental (or ESG) applications. As CTO of Blender Logic, he designed a semantic controller that improves the performance of machine learning applications that was selected as an exemplar of advanced AI algorithms by the DoD's Joint Center for AI (JAIC). Recently, Blender Logic teamed with sciGaia, a Montana-based provider of sustainability services, in order to produce a new generation of wellbeing-based planning systems. He is the author of "OLAP Solutions: Building Multidimensional Information Systems," which is used around the world in both graduate computer science and MBA programs, and of publications for both scholarly and IT journals.

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