Companies publish ESG reports with the intention of building trust among investors, stakeholders, and the public. But what if the data in these reports raises more questions than confidence due to anomalies and inaccuracies?

In recent years, several incidents of incorrect ESG reporting occurred in major corporations. According to Deloitte’s report, nearly half (46 out of 100) of the UK’s largest FTSE (Financial Times Stock Exchange) companies made revisions to their previously reported sustainability and climate metrics. 89% of these reinstatements were related to greenhouse gas emission metrics. Think about that for a moment—these aren’t startups figuring out their first sustainability report. These are some of the world’s most reputable organizations, and they’re getting their most fundamental ESG metrics wrong.

Why does it happen? What is the impact of wrong ESG reporting on an organization’s growth? And more importantly, how can you fix it? Let’s understand in detail.

Why ESG Data Anomalies Are a Serious Problem for Organizations?

The inconsistencies in ESG data impact businesses on many levels, such as:

1. Compliance Risk: Regulatory frameworks like CSRD (EU) or SEC climate disclosure rules (US) demand accurate ESG reporting data. If the ESG data contains inaccurate or missing metrics, organizations may have to pay penalties due to non-compliance.
   
2. Distrust in Investors: When the ESG reporting data is incorrect, investors lose their faith in the organization, which leads to delays in funding rounds. According to the Financial Time poll, around 70% of investors believe that incorrect data is the biggest barrier to ESG investment.
   
3. Inefficient Decision-Making: When the metrics are incorrect, management struggles to draw comparisons and make any informed decisions about the company’s new initiatives.
   
4. Financial Loss: Due to incorrect data, companies can get disqualified from the tenders that require ESG compliance. This leads to revenue loss. This is just one way to lose money due to incorrect ESG data. Many times, companies waste a significant amount of capital by investing in the wrong sustainability solutions due to poor reporting data.
   
5. Damage to Brand Reputation: When a company misreports ESG data, it impacts the brand image. Incorrect ESG data can indicate that the organization’s operations are not environment friendly or sustainable, and if that happens, they can receive a huge backlash from the public, which damages their brand’s credibility.
   
6. Limited Market Access: When companies fail to meet ESG standards, they may lose high-value partnerships and government contracts that prioritize sustainability. This limits their market access and growth opportunities.

Why ESG Data Goes Wrong – Root Causes of Anomalies

There are several challenges involved in ESG data management that lead to outliers and inconsistencies-

1. Lack of Unified ESG Reporting Framework

One of the biggest reasons behind poor ESG data quality is the lack of a single, global reporting framework. There are multiple ESG reporting frameworks available, such as GRI, SASB, TCFD, and CSRD. All of these frameworks have different structures and fields to manage ESG data. Since there are no uniform or specific guidelines on what ESG data points to collect or how to represent them in a standard manner, data suppliers collect some information while leaving other important data points behind. This makes data integration or consolidation challenging and leads to inconsistencies in data.

2. Supplier Data Quality Issues

Sometimes, the issues occur at the ESG data supplier’s end. If the supplier collects information from unreliable sources without validating them or doesn’t update the data time-to-time, the chances of inconsistencies or inaccurate data points increase. When companies aggregate and utilize such data, they end up reporting incorrect metrics. 

3. Data Silos

For ESG reporting, data is collected from various departments, including finance, HR, energy management, and supply chain. These departments extract and store information in disparate systems by following different methods, formats, and standards. As a result, data aggregation becomes difficult, and inconsistencies in ESG metrics arise.

4. Human Input Errors

Many organizations (especially those having complex supply chains) still lack automated systems to capture, process, and store ESG data. Due to the limited adoption of APIs, organizations struggle to pull real-time data from energy meters, supplier portals, or HR systems. They have to rely on manual data collection and entry methods. Their data teams manually copy details from emails, PDFs, and suppliers’ reports and enter them into CSV or Excel files, which often leads to typing errors. 

5. System Integration Failures

Even when organizations have automated systems in place, poor integration (or integration failures) between those systems can lead to inconsistencies in ESG data. For example, if one system fails to sync data due to a broken API or some other technical issue, significant data loss will occur. The ESG report still populates but with incomplete inputs. Similarly, if the integration logic is not updated alongside system changes (e.g., a new field added in the HR software), outdated data will be pulled from the system, leading to incorrect ESG reporting.

How to Detect and Fix ESG Data Issues before They Impact Your Bottomline

1. Regularly Audit ESG Data to Identify Anomalies at an Early Stage

When ESG data inconsistencies are detected at the initial stages, it becomes easy to fix them (before they propagate across reports, dashboards, or external disclosures). To do that, you must:

• Compare year-over-year or quarter-over-quarter ESG reporting metrics (carbon emissions, water usage, etc.) to identify any unusual or sudden spikes/drops.
• Set pre-defined limits on all the key metrics to catch data points that fall outside the expected ranges.
• Cross-check data from internal systems to identify misaligned values and incomplete or duplicate records.

2. Establish a Unified Governance Framework

Most of the time, ESG data issues occur because organizations lack a governance framework or fail to follow it diligently. To solve this problem, companies can:

• Define their own ESG data collection protocols, security standards, and validation and escalation rules. 
• Map their internal ESG metrics with any of the established governance frameworks, such as GRI, SASB, TCFD, and ISSB. 
• Ask the third-party data supplier (if they are involved in this process) to adopt the company’s internal taxonomy.

3. Leverage Reliable Automated Systems for Centralized ESG Data Management

Scattered data is error-prone data. To ensure that ESG data from different departments gets consolidated and synced in real-time, companies must:

• Invest in a reliable centralized platform that is compatible with their existing systems across departments.
• Implement automated validation checks to monitor the captured ESG data in real-time for inconsistencies, duplicates, and errors.
• Standardize data formats and units at the data ingestion level to eliminate manual conversions and ensure consistency across business functions.

4. Consider Outsourcing ESG Data Management and Reporting Services

The solutions shared so far demand time, expertise, and significant infrastructure investment. That is why many organizations these days are turning to reliable ESG data company for end-to-end support. These providers:

• Have governance framework expertise (GRI, SASB, TCFD, CSRD, etc.) to correctly map disclosures and avoid data inconsistencies.
• Implement advanced automation workflows for seamless ESG data collection, processing, and reporting.
• Have an internal QA team that cross-references and validates metrics at multiple levels before the final ESG data delivery.
• Use anomaly detection tools to identify errors or outliers before they affect ESG scores or compliance.

Here is a real-world example of how ESG data management services helped a European AI-powered platform to achieve ESG reporting accuracy while maintaining compliance. Unlike the 46 FTSE companies that had to revise their ESG disclosures, this European platform got it right the first time due to reliable third-party support.

End Note

ESG data quality issues are not something you can afford to neglect. For better compliance, credibility, and reporting, you need accurate, up-to-date, and reliable data that speaks highly of your company’s data management standards and protocols. Invest in the right governance framework, automated systems, or outsourcing companies to prevent non-compliance, damage to your brand reputation, and wasted resources.