Sustainability, ESG and the Changing Nature of Data
The current regulatory landscape is changing at a fast pace, and companies must keep up to stay ahead of the curve. An increased focus on the climate crisis and other environmental issues has created an urgency for data collection and processing to support ESG disclosure and sustainability management requirements.
Many companies address this challenge using existing data reporting processes. The same capabilities that produce an annual sustainability report, some internal dashboards, and perhaps a CDP or GRI report are being used to address these new requirements. This inevitably leads to poor outcomes.
The need for investment-grade data is well-documented. The commonly accepted characteristics of investment-grade data are accuracy, timeliness, completeness, relevance (materiality), and auditability. Achieving all five is challenging for many organizations, requiring processes and technology not currently in place. The challenge goes even deeper than this, however, as the data that is ultimately disclosed or reported is also utilized in unprecedented ways:
- Data will need to be audited by an independent third party and will often form part of the company’s annual report and financial statement
- Reporting produced using the European Sustainability Reporting Standards to meet the CSRD requirements must be tagged. This will use XBRL language to make the data machine-readable, so it can be stored in the European Single Access Point, providing a vast publicly accessible data store. This will greatly facilitate public access to corporate sustainability performance data, providing a high level of transparency and accountability
- Many companies struggle to address sharply increasing ad-hoc requests for data from a range of stakeholders, including customers, providers and ratings agencies. This requires a high level of data processing to respond to often unique data requests from many stakeholders
Role of automation
Workflow automation provides a way of drawing upon technological resources to address these issues. Leading EHS and Sustainability practitioners are increasingly adopting advanced solutions to increase efficiency, reduce costs, and ensure data quality.
Tools like document scanning for AI-enabled automated data capture and machine learning capability for processing large documents like utility invoices and supply chain data can make a big difference in driving workflow automation. For example, when it comes to priorities like Scope 3 emission measurement, automation can significantly help, considering the large volumes of datasets that need to be processed. Image scanning software can monitor real-time video feeds to identify and issue alerts for unsafe conditions or behaviors.
The internal review and third-party assurance processes before submission are also made easier by standardized and controlled workflows. This guarantees that disclosures are reviewed by specific stakeholders and that the investment community’s data control standards are met.
Workflow integrations streamline different application functions to ensure free and accurate data flow, allowing teams to access and utilize the information for their day-to-day work. Smart meters, operational plants, and other enterprise systems provide integration opportunities, offering efficient and reliable data flows into an enterprise EHS Sustainability platform. Disclosure and reporting requirements can all be addressed from a single consolidated data source, allowing the user to easily tailor responses as required in response to scheduled or ad-hoc disclosure requests.
Benchmark’s Data Exchange Portal Integrator TM (DXP) illustrates this application system well. It is a centralized platform that can import, transform, and output data from across the enterprise to multiple stakeholder units and ensures consistent data quality.
Another example is the CDP’s API, which enables accredited service providers like Benchmark Gensuite to make data submissions directly into the CDP portal from their ESG portal, avoiding any intermediate steps in the process. As a result, it allows users to allocate and submit records automatically as required by the CDP framework, consequently helping them save much time and reducing the need for manual data handling and editing per CDP format.
By utilizing proper sign-off and audit tollgates, end-to-end automation is made possible, including on-site data collection, emissions calculations, and direct submission of responses to the CDP portal. Occurrences of irregularities and errors from manual handling will be significantly reduced and even eliminated completely.
Finally, artificial intelligence tools can help generate insight from large datasets. Insights, real-time alerts, and action prompts can be generated using AI-enabled advisors that scan operations data and accelerate the data review process. AI-enabled site monitoring and real-time alerts and verifications can ensure safety and compliance.
Emerging technologies offer new and effective ways to manage the increasing challenge driven by data quality and volume requirements. Companies that don’t adopt this technology will be increasingly exposed to risks related to cost and efficiency, disclosure of incorrect data, and reputational damage.
About the Author
Peter is Director of Business Development at Benchmark Gensuite. 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.