Why and How Executives Must Incorporate Their ESG Performance Data Into Corporate Strategy

Business leaders have come to expect that capital markets will reward them for collecting, managing, and regularly disclosing investment-grade data that describe their organizations’ management of financially relevant Environmental, Social, and Governance (ESG) “risks.” And while it’s promising to see corporates rising to the occasion, evidence is mounting that this is nonetheless an unsustainable arrangement—at least in its current form. 

First, on the part of investors, there’s the failure to stamp out emerging skepticism. The concerns of their clients and, increasingly, policymakers and regulators over whether there is a clear causal relationship either between investee companies’ ESG and financial performance outcomes, or even between investee companies’ ESG performance and their attendant sustainability outcomes, are hotly debated. Relatedly, second, on the part of corporate practitioners of ESG, there is an apparent failure to furnish the evidence that investors can use to combat this so-called ESG “backlash.”

But it’s not for lack of trying. The trouble has to do with a host of factors outside these roleplayers’ control. Chief among these is the lack of globally consistent, universally applied standards for the metrics and methods that companies use to measure and disclose their ESG performance, let alone identify the sustainability risks that warrant their attention. It’s then up to investors to employ bespoke, oftentimes opaque methodologies to reconcile the irregular and incomparable disclosures these circumstances yield.

This is not to say, however, that corporates are helpless. On the contrary, executives can provision their investors with the ESG performance information they need and, in the process, advance their organizations’ sustainability and bottom-line outcomes with a change in approach. Rather than treat the collection and reporting of accurate, contemporary, complete, financially relevant, and auditable ESG performance data as a box-ticking exercise, executives must see the information these activities yield for the managerial resource that it is.

For executives, this entails first operationalizing a thoroughly stakeholder-influenced enterprise ESG program. And this program must be undergirded by a robust, cloud-supported ESG performance data management and reporting platform. This will ensure executives have consensus over their companies’ targeted ESG outcomes, achievement strategies, and key performance indicators (KPIs), as well as the automatically collected, collated, and stored streams of investment-grade ESG performance data needed to at least describe actual performance outcomes and report it to stakeholders.

Graduating from ESG performance monitoring and reporting to effective, stakeholder-appeasing, bottom-line advancing, strategic ESG performance management, however, will require executives to extract actionable, forward-looking insights from their records of past performance.

Indeed, a future-proofed enterprise ESG program is one that’s informed by decision-driven data analytics. This is the inverse of data-driven decision-making, whereby operational data is collected and analyzed with the express purpose of informing specific, predetermined managerial and investment decisions, rather than randomly executing ad hoc decisions informed by haphazardly derived insights.

For the ESG aspirant, the objective of this process is, plainly, is to ascertain which ESG performance-related management and investment decisions advance enterprise progress toward targeted sustainability outcomes, and those that don’t. Perhaps obviously, this an insight that will bring efficiency and effectiveness to the enterprise ESG disclosure program. And while it may sound daunting, executives must remember that their investment-grade ESG performance data is the foundation of the “decision-centric data” needed to execute this process.

The key is tracking ESG performance outcomes over time against various benchmarks (i.e., industry competitors, neighboring businesses of similar size, the expectations of various stakeholder groups, etc.); regularly regression analyzing the relationships between ESG inputs (i.e., internal policies, targeted investments, etc.) and both ESG performance and bottom-line outcomes, and; recording their findings in the cloud-based data management platform’s centralized, remotely accessible digital system of record for retrieval, audit, and reference later on.

By way of example, take the case of a transportation logistics company that has committed to achieving net-zero operational emissions within 10 years. Using a conventional tick-the-box approach, this firm will presumably be able to use their utility and vehicle fueling bills to complete annual disclosures that at least describe the energy consumption of their facilities and vehicle fleets within the preceding 12 months. With official conversion factors and basic arithmetic, both the logistics company and the reviewers of their disclosures—namely investors—would be able to monitor the company’s progress toward its goal with each successive disclosure.

Clearly, this unsophisticated, discrete snapshot of our logistics company’s ESG performance is untenable, both for the company’s sustainability goals and their audience of increasingly anxious investors. By relying on static, backward-looking data describing actual ESG performance outcomes alone, our logistics company would be hard-pressed to confidently (and measurably) accelerate achievement of its net-zero emissions goal without compromising either their performance against other “E,” “S,” or “G” issues, or worse, their bottom-lines.

Instead, our transportation logistics company ought to consult with their stakeholders to build consensus over interim goals and orchestration of supplemental achievement tactics—a set of discrete, predetermined decisions—and proceed to collecting and analyzing the corresponding decision-centric operational data needed to execute them.

For instance, the company may elect for some combination of energy efficiency retrofits of their building stock and vehicle fleet electrification at the outset of their campaign. The emissions-reducing effects of these measures, extrapolated from the subsequent utility and vehicle fueling bills housed in the cloud-based platform, will need to be appraised in the context of their corresponding capital outlay, operational energy cost savings, alignment with stakeholder expectations, and impacts on the company’s management of other ESG issues, among numerous other variables.

In short, business leaders will need to use actual performance outcomes across each of these areas to determine which emissions-reducing measures to maintain, modify, or retire and substitute altogether. For instance, if the electrification of the vehicle fleet and, in turn, new reliance on inadequate charging infrastructure disrupts the company’s ability meet its operational performance objectives, then the company may be inclined to look for alternative emissions reduction strategies.

Alternatives may include energy efficiency retrofitting a larger portion of their building stock, requiring that their corporate employees return to their offices rather than consume energy at home, opting for alternatives to fleet electrification (e.g., fuel-switching to compressed natural gas), or purchasing an array of verifiable carbon offsets. Come what may, any decision will need to be supported by robust, forward-looking, analytically derived estimates of how they will affect ESG and financial performance. And the cloud-based platform will need to be employed to ensure that these decisions’ attendant outcomes continuously align with both stakeholder-agreed interim targets and the overarching campaign of achieving net-zero operational emissions within 10 years.

It’s by leading with the decisions that need to be made, rather than formulating decisions upon the data at hand that executives will be able to operationalize a more effective and resilient enterprise ESG program. And it’s by affording the enterprise ESG program the decision-centricity it merits that executives will be better able to incorporate their sustainability priorities into their overarching business strategy.

Together, these are practices that will help companies refute the capital market’s and regulators’ emerging concerns that ESG performance isn’t “real.”

About the Author

Peter is an EH&S and Sustainability professional with 25 years’ experience across a diverse range of geographies and roles. His expertise encompasses the full range of EH&S and Sustainability aspects, including socio-economic planning, environmental management, and corporate sustainability performance. He has developed specialist expertise in the use of technology to drive operational excellence and resource efficiency and has implemented data and process management systems for numerous global clients. Peter has worked for a range of clients across Australia and Europe, in the industrial, manufacturing, pharmaceutical, resource and consumer goods sectors. His professional focus is to help companies use EH&S and Sustainability technology to drive improved business performance.