The Next Wave Of Automation: ESG Data
The raison d'être behind automation is efficiency. We’ve watched Manufacturing 2.0 springboard off innovative architecture to futuristic factories reliant on robotics, cloud and edge computing, artificial intelligence (AI) and other Internet of Things (IoT) connectivity. Likewise, we are witnessing Industry 4.0 underway riding a broader application of intelligent tech across industrial sectors, deploying automation to tee up streamlined operations that yield higher productivity at lower costs.
What’s on deck then, with regard to the next wave of automation? I believe the answer is a topic on the tip of many tongues as evidenced by the World Economic Forum’s 2021 Davos conference agenda, that of Wall Street and the general public’s desire for a better world — environmental, social and governance (ESG).
In January 2021, Larry Fink, CEO of BlackRock, the world’s largest asset manager with $8.7 trillion in assets, issued specific directives calling on firms to align with global efforts to reach net-zero greenhouse gas emissions by 2050. Details include “the need for better data to improve disclosures of emissions and set rigorous short, medium and long-term targets to reduce them... crucial for investors to track progress and identify companies that are leading the energy transition.”
2020 saw more than $47 billion, double the amount of the previous half-decade, go toward investment strategies that prioritized ESG. This jump is further compounded by an uptick in stakeholder capitalism revolving around the idea that companies are responsible to their shareholders, but also to society at large. ESG as a field is centered on the belief that businesses should create not only economic value, but also social value.
My organization is an industrial smart contract network that operates via blockchain, and I've seen how ESG data has immense potential for more accurate collection by using blockchain technology. Current ESG is marred by barriers — inaccurate or poor quality data, burdensome admin layers and intensive time and resource commitments. Automation of ESG measurements could bring more ease and accuracy for trust and compliance.
Focusing On Sustainability Metrics
Numerous companies have publicly declared ambitious carbon neutral pledges — Apple committed to 100% carbon neutrality for its supply chain by 2030; likewise, Microsoft announced its plans to be carbon negative by the same year; Amazon created The Climate Pledge, a group for sustainable businesses to commit to net-zero by 2040, 10 years ahead of the Paris Agreement, currently with more than 50 major companies; Verizon, IKEA, Delta, BP — there’s no shortage of climate promises spurred largely by climate change concerns and investor demands.
In asset-heavy industries, momentum is building behind renewable energy, lowering and offsetting carbon, broader sustainability endeavors and energy transition. Operators are setting carbon-reduction targets, looking for ways to reduce emissions and decrease climate-related business risks — ExxonMobil was the first oil supermajor to disclose greenhouse gas emissions data and said that it will provide annual emissions reports. Shell aims to be net-zero on all emissions from manufacturing by 2050 or sooner and to reduce their carbon footprint by 65% on its energy products, and plans to help its customers decarbonize. BP is taking an active stance to help get the world to net-zero and anticipates achieving this for itself by 2050; Equinor announced an ambitious investment in renewables, emissions-cutting from oil and gas activities and alignment with other industry giants on the 2050 net-zero target date. (Full disclosure: Data Gumbo received equity funding from Equinor Technology Ventures.)
While many of these companies plan on sharing data reports yearly, these "greener" goals share little information or methodologies about how companies anticipate executing against these pledges. To track and produce sustainable ESG reports, companies should be able to generate accurate, auditable data and accountable records that can prove sustainability improvements. That’s where blockchain comes in.
Automation And ESG Data
Blockchain has long been hailed as the great beyond of the internet; though one that often gets trapped in its own hype around crypto. The real value of it lies in its inherent ability to retain immutable, auditable records of data and events across participants, counterparties, vendors, suppliers and customers. In ESG measurement scenarios, blockchain provides a foundation for accurate data across supply chain management. Instead of operating on obscure promises from counterparties to engage in better environmental practices, blockchain lends both accountability and accessibility to data aggregation to create a comprehensive picture of the true environmental impact.
Insights into a company's supply chain can be collected (potentially through smart contracts for operational field data), and that information and data can then be used to enable automated transactions and capture ESG data.
Currently, the variegated quality and quantity of data companies collect for ESG reporting is uneven with insufficient data harvested from third-party providers and a general lack of uniform guidelines or disclosures, according to the Wall Street Journal (paywall). This poses significant challenges to understanding ESG impact overall. Blockchain can reach across a supply chain into data sources, measurements and siloed counterparty information to capture and verify real-world data.
Riding The Wave
The future of ESG success lies in the technology that underpins its abilities to accurately and automatically measure and track performance, and thus make improvements, as companies in all sectors are held accountable to higher environmental standards across stakeholders.
However, there are some challenges and roadblocks to consider for ESG automation:
• Buy-in across the organization
• Change management
• Slow-moving, entrenched industries lagging to embrace digital transformation (like the energy industry)
• Bad data or poor quality data
• Issues with integration capabilities with existing systems
Business leaders should keep these in mind when considering adoption.
As companies vie for positive share pricing, better resilience and greater adaptability, and areas of focus rapidly accelerated by the Covid-19 pandemic, the coming wave of ESG data measurement automation will empower companies across supply chains to achieve environmental sustainability goals and comply in an increasingly hyper-transparent world. As it stands, the broader world will benefit from better ESG data, including from the companies working to reduce their carbon footprints both for altruistic good and in jockeying for a better financial position.
This article, authored by Andrew Bruce, originally appeared at Forbes Technology Council.