Why big data matters for ESG

Best Practices ESG Sustainability Reporting
  • May 14, 2021 | Ryan Nelson
Why big data matters for ESG

Why big data matters for ESG

In 2006, mathematician and data scientist, Clive Humby coined the phrase “Data is the new oil.” 15 years ago, many companies would have considered sharing data about their environmental footprint, energy use, or board composition a risky and difficult; today, data is becoming a business imperative.

As investors become increasingly focused on sustainability issues, they are demanding greater transparency from companies in the form of concrete data. The need for data is so great, the World Economic Forum estimated that, by 2025, 463 exabytes of data will be created each day globally, the equivalent of 212,765,957 DVDs per day.

Investors and hedge funds are utilizing this data together with traditional analysis to identify sustainable investment opportunities with lower financial risk. In fact, some data platforms are now being developed to calculate monetary values for companies’ non-financial externalities, such as ESG (Environmental, Social and Governance) factors.

However, despite the large amounts of data available, investors often struggle to discern the value of the information provided. The data may be vague, biased, and inconsistent, or it may use a variety of non-uniform benchmarking standards or rating scales. Michael Palmer explained it best when he expanded on Humby’s quote by saying, like oil, data is “valuable, but if unrefined it cannot really be used.”

Understanding the big data revolution’s impact on ESG

Data technology and our ability to analyze large amounts of data is growing at exponential rates. Artificial intelligence and machine learning, computational strengthening, and increased global connectivity are driving what many are calling the “big data revolution“. Essentially, technology is enabling companies to collect detailed information from and share information with their consumers, suppliers, partners, and competitors.

ESG data includes any indicators that shed light into the sustainability context of an asset, facility, company or region, whether historic, current or expected. ESG data is collected under three primary umbrellas:

  1. Environmental data should capture environmental information such as annual carbon emissions and energy consumption, water usage, waste and pollution output, and more.
  2. Social data focuses on statistics related to workforce diversity, gender equity, human rights, and more.
  3. Governance data tracks company input regarding corruption, labor practices, gender composition of the board of directors, and more.

While all ESG data is important, much of the world is focused heavily on environmental sustainability and reporting as climate change becomes a global risk that affects every country on the planet and disrupts economies. While major damage has already been done, it is possible to use big data to generate useful insights that can support environmental sustainability and help companies improve business performance by acting on the environmental impacts of their operations throughout the value chain.

For example, the private sector continues to make impactful environmental decisions and commitments to sustainability in their supply chains. Examples include:

  • Nestlé’s efforts to reduce the weight of their packaging since 1991 (with a reduction of over 500 million kg to date).
  • Walmart’s goals are to create zero waste, operate with 100% renewable energy, and sell products that sustain our resources and the environment.
  • Honda’s goal to reduce the CO2 emissions intensity of motorcycles, automobiles, and power products by 30% compared with 2000 levels by 2020.

Yet tracking the full supply chain for large corporations and keeping companies accountable to their goals requires the use of big data analysis, especially when balancing multiple objectives such as reducing waste and increasing profitability.

As big data technology improves, and companies can use platforms to track and integrate qualitative data into their operations, businesses and investors alike will be able to better couple big data analytics and sustainable business practices.

So, what’s the big ESG data problem?

While there is an enormous amount of data available, the different kinds of data, inconsistency of information, and varied benchmarking and analysis methods remains a problem. Additionally, the lack of transparency among data providers about peer group standards and concert ranges for ESG metrics creates market-wide inconsistencies, undermining the reliability of the data.

ESG researchers and analysts, as well as investors, have to deal with large “data gaps” in ESG metrics that span across industries and time periods. Disagreements exist among data providers who have different gap-filling approaches that can lead to big discrepancies and inaccurate, inconsistent ratings.

There are three tools that can help address these data issues:

  1. Quality data: Transparent communication and strategic goal tracking can only occur when stakeholders have access to reliable, material, high-caliber public data.
  2. Benchmarking: One tool that proves essential in solving these data issues is benchmarking. Benchmarking is a process by which data providers define companies’ peer groups, definitions that are crucial in determining the performance ranking of a company.
  3. Standardized reporting & disclosures: Holding industries to the same disclosure requirements and moving to a single global reporting standard can ensure sustainability information from companies will be consistent and aligned.

Companies can begin to control their ESG data narrative by proactively customizing their metrics and developing clear disclosures. Companies within different industries can also work together to self-regulate by agreeing on a baseline of ESG metrics with industry peers in order to achieve comparability. Lastly, companies can embrace global reporting standards and resources such as the TCFD recommendations and the SASB standards to help improve disclosure of climate-related risks and opportunities.

Benefits of data tracking

Data tracking and analysis has many benefits for companies, investors, and regulators, such as:

  • Companies can use data to showcase business performance, demonstrate improvements, track goals and commitments, all of which build brand sustainability and trust with investors and consumers.
  • Investors need solid information and strong management strategies founded on high-quality, consistent data and reporting that ensures companies are positioned to thrive and guarantees sustainability in the face of social, economic, and environmental upheaval.
  • Big data can also provide big benefits for regulators who can integrate statistics into government policies to ensure better environmental regulation. In fact, governments have access to sensor technology and real-time reporting data that can be used, for example, to monitor emissions of large facilities and help design regulatory frameworks.

Ultimately, using data to monitor and track the impact companies have on the natural world provides an innovative way to ensure business embrace sustainability efforts while creating change, cutting costs, and boosting long-term profitability. Today’s data allows us to detect sea level change, identify resource usage, track global temperature change, and create future projections. Investors, companies, and governments all must commit to using big data analysis and enacting sustainability agendas to ensure humanity can be sustained safely and successfully on our planet.

ESG materiality assessments

With investors inquiring more and more frequently about what your company is doing in regard to responsible investment, how you treat employees and vendors, your dedication to sustainability initiatives, and other activities that fall under the ESG umbrella, it’s important to have answers to these questions.

An ESG materiality assessment empowers you to easily report on your current state and outline future initiatives while taking into consideration your business goals and risks. Download our guide to creating and extracting the maximum strategic value from an ESG materiality assessment.

Download guide

Ryan Nelson

Ryan Nelson is the Co-Founder and CEO of Goby. He has over 20 years in enterprise software and management consulting experience, including supply chain software implementation and process optimization for fortune 50 companies. Since 2009, Ryan has been focused on helping companies amplify their ESG impact with technology.

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