In the not-so-distant past, profits and shareholder value trumped all other concerns for corporations. But with climate change triggering more frequent and severe natural disasters and wide gaps in diversity and wealth distribution at the forefront of public discourse, a new generation of buyers has put increasing pressure on companies to do more.
Today, enterprises must prove they’re positively impacting the world. ESG reporting – reporting on environmental, social and governance criteria – is how businesses demonstrate these positive contributions.
And as ESG has grown in popularity, so too have the uses for ESG data.
The Value of ESG Data: Use Cases
ESG investing, once a niche area called ‘green’ or ‘ethical’ investing, has grown significantly since 2015. A recent study found U.S. survey respondents across finance, banking, and insurance reporting that three-quarters (76%) of their organization’s investment decisions are impacted by ESG factors, with 67% in the U.K. reporting the same.
Continuously evolving regulations are also driving new uses, particularly in Europe, which has the most sophisticated ESG regulations to date. For example, under the new Sustainable Finance Disclosure Regulation (SFDR), banks will need to use ESG information as part of their customer onboarding process — specifically, for Know Your Customer (KYC) — as they’ll have to report on their green asset ratio.
ESG Data Integration Challenges
To inform investment decisions and offerings for their clients, financial services and investment firms require access to ESG data and scores. Since many companies don’t report all of the information firms need, they have to cross-reference and combine corporate ESG reports with other data sources like internal assessments/ESG data hubs and third-party providers of ESG scores (e.g., S&P Global ESG Scores). Invariably, each data report is built on different standards, at different frequencies, and using inconsistent data formats, which can lead to data quality nightmares upon integration.
The same can be said for the various data sources enterprises use when compiling ESG data for reporting. Covering a vast amount of territory, from HR to physical sensors to EMS systems and beyond, data is sprawled across the organization — some in modern systems, some in legacy systems too valuable to replace (like the mainframe), and still more in third-party systems, in a variety of formats.
Integrating core enterprise data into ESG reports consistently and accurately is easier said than done. And time is of the essence. Markets move fast, and the regulatory landscape changes constantly. Businesses that want to keep up must adapt to an agile ESG reporting method. The World Economic Forum (WEF), which reports that the number one ESG challenge organizations face is data, says, “Reporting, ultimately, should be a by-product of an ESG program where real-time data is integrated into decision making on a continuous, ongoing basis.”
But most organizations aren’t in a place to deliver continuous data yet. Existing data integration tools — point solutions that handle only a narrow range of requirements, tools from cloud providers that create vendor lock-in, and products focused on integrating data from SaaS apps that don’t address legacy systems — leave gaps that require hand coding and one-off implementations. As data volumes grow and technologies evolve, so does the risk of pipeline breakage. Teams end up spending enormous amounts of time troubleshooting problems and recoding broken pipelines rather than delivering on new data requests. In a recent study of over 650 data leaders and practitioners, 68% of respondents said this kind of data integration friction prevents them from delivering data at the speed of business.
How Resilient, Repeatable Data Pipelines and Modern Data Platforms Accelerate ESG Reporting
As data continues to grow in volume, complexity, and urgency — and as data platforms continue to change and proliferate — data integration friction is only increasing. But there’s a way to eliminate this friction and make ESG data continuously available for reporting and decision-making as the WEF recommends.
Resilient, repeatable, and scalable data pipelines like those built with StreamSets, allow easy and secure connections to common ESG data sources to ingest and transform ESG data and move to modern data platforms like Snowflake. With StreamSets your pipelines:
are designed to keep up with constant change, managing data drift with ease
flexibly run across on-premises, hybrid, cloud, and multi-cloud environments
have a centralized control hub for management and monitoring across environments
alert you to hidden problems in data flows so you can address performance, data leakage, quality, and other risks before they affect the business
and come with a pre-built data processor, simplifying data transformations
Challenges like inconsistent data formats and broken pipelines become a thing of the past, leaving you to focus on continuous ESG reporting and improvement.
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