How Data Analytics Can Boost Your ESG Performance

Compared to a decade ago, many businesses now have an active ESG program in place.

Growing pressure from governments and investors, changing customer demand patterns and an increasingly conscious customer base have accelerated the adoption of these programs. 

But are these programs achieving the desired objectives? 

How are businesses checking the program’s progress and effectiveness? And how can investors evaluate this aspect of business operations that is increasingly crucial for their investment decision?

In addition to outlining the company’s sustainability goals, the ESG program assesses the existing state of operations and sets key parameters for measuring effectiveness. The evaluation of these parameters requires the business to first collect and then accurately analyze a huge amount of data. This is where they need a data analytics solution that can quickly decode all this data and present actionable insights. 

To accurately measure Scope 3 emissions, for example, a business must collect emissions data from its supplier base. Once this data is collected from suppliers across the supply chain, it can be analyzed with the help of an analytics solution. 

How Investors Assess ESG Performance 

ESG data analytics can help investors make informed investment decisions by providing information about a company’s ESG performance. 

Let’s first look at how investors assess a company’s ESG performance when these analytics solutions are not available.

1. Sustainability Reports: 

Investors look at a company’s sustainability report to learn how they are performing vis-à-vis their ESG goals. A key problem with these reports is that they are published annually and may include outdated information from the previous year. Secondly, there isn’t really a way for investors to cross-check the data and information mentioned in the report. At times, information presented in the report may be insufficient or subjective. 

2. ESG Ratings: 

Investors assess ESG performance by looking at ratings assigned by ESG rating agencies. Each rating agency follows a unique approach which is not disclosed to investors. For example, two rating agencies may assign two different ESG ratings to the same company. This can confuse an investor seeking reliable information for making an investment.

How Data Analytics Benefits ESG Reporting and Monitoring 

Firstly, data analytics helps businesses gather ESG data from disparate sources, such as internal teams, external suppliers, and various databases that may store ESG-related data. Next, data analytics can identify and correct any data errors, inconsistencies and missing values. 

Data analytics can now derive meaning from the huge volume of data, which is mostly unstructured and generated from various sources. By crunching data from supply chains, sustainability initiatives and social impact programs, it can measure the effectiveness of the ESG program. 

It can also help a business spot trends and identify specific areas of improvement. For example, data analytics can help your business measure energy consumption in operations and identify functions where you are using more energy than required. You may need to optimize HVAC systems, upgrade equipment or implement more energy-efficient practices. 

Likewise, data analytics can help draw a comparison between the energy consumption of your business to your peers in the industry. Such benchmarking can further identify areas where you can improve performance. 

ESG programs require greater collaboration with external partners in the supply chain. As a responsible business, you want to ensure that you do business with suppliers who share your concerns and are ready to work with you to achieve the goals. This is another area where data analytics can help. It can look at suppliers’ ESG data and labor practices to check their progress. It can also identify suppliers who are not adhering to the requirements and suggest corrective action. 

Build Predictive Models for the Future 

Your business may be using data analytics to get a clear picture of your current ESG performance. The question now is: How can you improve this performance? 

Data analytics can help in this endeavor too by using current and historical data to build predictive models. A data analytics solution can access a wide range of data points, such as emissions, energy consumption and supply chain performance data. It can employ statistical techniques or machine learning algorithms to build a predictive model for the future.

For example, it can estimate carbon emissions in the next five years based on current production, energy consumption and other relevant data. 

Finally, AI and machine learning models can constantly evolve and be trained on various ESG datasets as well as regulation. These models can allow businesses to anticipate potential risks and opportunities. 

GEP GREEN can help you measure and advance your ESG progress. By integrating transaction data, it can correlate ESG data with your spending patterns for informed decision-making. Learn more.