In today’s data-driven world, the importance of data quality cannot be overstated. Accurate and reliable data is essential for informed decision-making, allowing businesses, organizations, and individuals to gain meaningful insights and make well-informed choices. However, upholding high-quality data can present challenges, especially in areas that have not undergone thorough scrutiny before.
Let me explain.
ESG reporting is relatively new for many organizations, and even those reporting certain metrics face higher expectations and scrutiny than ever before. As a result, ESG reporting processes and data quality are struggling to keep up with these expectations. Getting it wrong could be catastrophic.
Header: The Reputational Risk of Inaccurate Data
Publishing inaccurate data not only jeopardizes the credibility of information but also poses significant reputational risks. Organizations that release flawed or inaccurate data may experience a loss of trust among stakeholders, leading to long-lasting effects on their reputation and relationships with clients, partners, and the wider public. Therefore, it is crucial for organizations to prioritize data quality and scrutinize information, particularly in areas not previously reported externally, to avoid potential risks and maintain credibility.
In this blog, we will discuss five ways to improve ESG data quality and integrity. But first, we need to understand what is meant by data quality and its importance:
Understanding Data Quality
Data quality measures the degree to which data is accurate, complete, consistent, reliable, and timely to meet its intended purpose. By upholding high levels of data quality, organizations can maintain trust in data-driven processes and prevent potential errors or inaccuracies that could undermine the value of data.
Importance of Data Quality
Ensuring data quality is vital for organizations to gain meaningful insights and make well-informed decisions. By maintaining high levels of data quality, organizations can retain trust in data-driven processes and communications and prevent potential errors or inaccuracies that could undermine the value of data.
Clearly, data quality is important, so how can you improve it?
How to Improve ESG Data Quality
- 1. Robust internal controls:
Establish a robust internal control system for capturing data at the initial recording stage. Most large organizations have expertise in accurately capturing data in the financial reporting infrastructure. Similar practices should be applied to recording activity related to ESG matters. This involves documenting and standardizing processes, validating data, implementing access controls, performing data reconciliation, and providing staff training.
- Eliminate manual work and spreadsheets:
Eliminate manual work involved in managing and moving data, including the use of spreadsheets. Manual processes increase the risk of human error, while spreadsheets can become fragmented, difficult to audit, and prone to mistakes. Moving away from manual processes and spreadsheets helps improve data accuracy and avoid costly problems resulting from data errors and inconsistencies. According to a survey by Forrester Research, data errors accounted for an average of $14.2 million in losses per year for organizations. (link)
- Automate processing:
Implement an automated processing system for reporting and management information to ensure consistent preparation and reduce the risk of errors. This is a necessary step in response to eliminating manual work and reliance on spreadsheets. By establishing an automated processing system for reporting and management information, organizations can benefit from improved accuracy, enhanced efficiency, real-time reporting, standardized practices, data integration, scalability, and data security. These advantages contribute to more effective decision-making, streamlined operations, and improved organizational performance.
- One source of truth:
Strive for “one source of truth.” Establish a practice of having a single, authoritative, and trusted version of data or information within the organization. This means designating one source that holds the most up-to-date, accurate, and reliable data, serving as the reference point for informed decision-making and business operations. Achieving one source of truth requires effective data governance, data integration technologies, a master data management strategy, and a focus on data quality control and monitoring.
- Audit:
Subject the data to internal and external audits to identify weaknesses in internal controls and provide recommendations for improvement. Conducting audits enhances accountability, identifies and mitigates risks, improves compliance, identifies process improvements, increases confidence and trust, and fosters organizational learning. These benefits contribute to overall organizational effectiveness, efficiency, and success. The value of audits is reinforced by the requirement of the EU Corporate Sustainability Reporting Directive, which will require assurance and the expected directives coming from the Security and Exchange Commission.
Conclusion
The attention to ESG data and reporting is growing, and organizations are expected to publish more accurate and comprehensive information. Areas of the business that have not undergone the same scrutiny as financial reporting may be more prone to error. Companies need to respond quickly, as there are reputational and legal risks involved.
While numerous solutions are available, it is crucial to focus on what your business needs to achieve ESG excellence. Automating data collection, integrating systems, automating processes, developing quality checks and having auditable processes can be addressed with the right technology, opening up opportunities for organizations to move faster and more efficiently.
Solve your most complex data collection and consolidation problems by transforming your IT space into a well-oiled and highly-efficient machine. Speak to us about automating your ESG data collection and preparation processes for peak enterprise performance.
