Driven in large part by a growing awareness of the effects of unchecked carbon emissions, environmental, social, and governance (ESG) initiatives have been gaining momentum across companies in Europe and, more recently, the U.S. Some verticals, notably financial services, are beginning to tie ESG information directly to investment decisions, while all companies are realizing that a strong commitment to ESG is necessary to attract and retain today’s consumers and business partners. 

While there are many ways to build, support, and develop an ESG initiative, one impactful way to streamline and dramatically accelerate such an undertaking is by managing data more effectively.  

Data Management and ESG

ESG relies on a steady stream of reliable, trusted data. However, even in this age of big data and cloud, many companies continue to struggle with integrating data between different systems, business units, business functions, and geographies. Much of the data needed for ESG reporting is stored in functional silos, integrated only by replicating it to a central repository via batch-oriented extract, transform, and load (ETL) processes. As a result, data will be available for reporting at different times, depending on where the data is in the replication process relative to other data, so there can never be a single, authoritative source of truth. 

When data is siloed in this manner, it impedes Data Governance, which, in turn, impedes the broader governance in an ESG initiative. To implement data security and governance controls across the enterprise, administrators have to manage each data source individually, which is extremely time- and labor-intensive. That slows down the implementation and operationalization of ESG initiatives, as processes such as getting management buy-in for ESG initiatives, identifying and addressing ESG skill gaps, and choosing the most effective ESG KPIs become complicated without readily available data and insights.

Logical Data Management and ESG 

Logical Data Management solutions provide a modern approach to Data Management, which overcomes the limitations of traditional approaches. Powered by data virtualization, logical Data Management solutions do not physically replicate data. Instead, they enable stakeholders to logically connect to data in real time, no matter where it may reside. Implemented as a company-wide data-access layer above a company’s diverse data sources, the data virtualization layer itself contains no data, but only the metadata necessary to access the various sources. 

Because a data virtualization layer centrally stores metadata, companies can leverage this to implement data security and governance protocols only once and have them be immediately applied across the entire organization’s myriad data sources, in real time. 

With data virtualization, organizations can establish business-friendly semantic layers without affecting the underlying data sources. 

For ESG initiatives, logical Data Management solutions can: 

• Enable seamless ESG reporting across a company’s different data sources, in real time, without having to replace any existing hardware
• Provide direct monitoring and control of machines and industrial processes
• Support data catalogs that not only list all available data assets but also provide access, right from the catalog
• Encourage data democracy through interfaces that appeal to both technical and business users
• Simplify development by enabling stakeholders to build functionality at the data virtualization layer, without affecting the underlying data

Finally, logical Data Management solutions are “intrinsically green.” Not only do they reduce the need to physically replicate data, which requires a hardware footprint, but they also require less processing power because, by design, they employ the most efficient query for each operation. 

The Festo Story

Many organizations are becoming increasingly conscious about the ESG impact on how they are running their businesses. One such organization, Festo, an independent, family-owned company established in 1925 and based in Esslingen am Neckar Germany, is a driving force in automation. Recently, the company needed to modernize its systems to optimize operational efficiency, automate a variety of key manufacturing processes, enable self-service data access, and most importantly implement an energy-efficient manufacturing process. However, Festo lacked an agile, effective way to integrate the data from its existing silos, which included a data warehouse, machine data sources, and other data sources that are critical to meet its business objectives. 

Festo implemented a logical Data Management platform powered by data virtualization, to deliver enhanced insight without having to physically move data; simplify data consumption; quickly integrate new data sources, making them available to user communities in real time; facilitate smarter decision-making via additional information-enrichment capabilities; and increase the speed and agility of both business and IT. With the implementation of the logical data management architecture, Festo was also able to deliver dashboards and visualizations of energy KPIs that enable shop floor teams to gain instant visibility, engage in active monitoring, and ultimately drive energy-saving efficiencies.

ESG Reimagined

Sustainable business practices are becoming norms for many enterprises, as they are being measured by not only their financial outcomes but also how their business impacts society in general. While enterprises may sometimes feel reluctant to implement ESG initiatives for fear of slowing down their business, implementing an effective, actionable ESG initiative might not be as time-consuming or complex as you might think. With a steady flow of real-time, trusted data, organizations will have the tools to not only begin an ESG initiative but also to realize its goals in the most efficient way possible.

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• Source: https://www.dataversity.net/logical-data-management-for-environmental-social-and-governance-esg-initiatives/