Environmental, social and governance (ESG) data integrity solutions

Let’s look at the big picture. Before ESG became a “household name” within the realm of business imperatives, many organizations were already making efforts to be environmentally friendly and inclusive.

But even if you’ve been doing this all along, how are you quantifying those sustainability efforts? Do you have a way to seamlessly and efficiently identify, extract and aggregate the granular data you need to produce impactful reports?

While environmental, social, and governance priorities will vary from one organization to the next, there are often a few big commonalities: reporting on ESG efforts are manual, time consuming, and costly processes.

Organizations need a flexible framework to efficiently identify, understand, and link the underlying data elements required for accurate, consistent, and contextualized ESG reporting.

But visibility that does not include data quality scores and metrics, including real-time data observability leaves you at risk of reporting and data insights that are not accurate.  This leads to lack of trust in your ESG metrics that will impact not only the decision-makers within your organization, but investors and customers that are tracking your ESG analytics.

Ask yourself if your data …

• Is accessible across legacy and modern systems for complete reporting
• Can deliver the outcomes you need with timely tracking and scoring metrics
• Is easily found, understood, and linked to critical ESG KPI’s
• Is trusted with optimal quality and health to identify risk and improve business outcomes

Many organizations aren’t there quite yet – and data integrity is what can take things to the next level.

With more cost-effective data quality processes, time-saving automation of manual efforts, and overall greater confidence in data trust, you can be sure that your data-driven ESG reporting is making the impact you need it to.

Equally as important as reporting on your efforts after the fact, is having the ability to accelerate your decisions in real time. Innovative organizations understand that data leveraged for ESG is frequently critical in other business operations and analytics. Understanding the relationship of ESG data to related business processes exponentially increases the value of visibility and improving overall data trust. Data governance that illustrates relationships through data impact and lineage is critical to expanding the value of your ESG metrics and reporting.

Organizations have found that the lower the real-time visibility, the greater the risk for potential negative ESG ratings that could result in expensive fines, bad press, and a loss of investors, customers, and top talent.

Alternatively, having that real-time visibility means more insight and protection of your key performance indicators (KPIs) and metrics. When you can identify risks as they’re happening, there’s more opportunity to act upon them and ensure positive outcomes.

Take, for example, the case study of a major consumer product corporation. The company needed a unified data platform that provided data quality and a data catalog to enable real-time visibility for ESG operational value.

Why? It was discovered resource usage of one of their production plants was significantly more than other plants. With greater visibility into ESG KPI’s, the company can move forward with more sustainable, proactive business evaluations – making it easier to spot and remedy similar problems as they’re happening, rather than after the fact.

Along with enhanced reporting and real-time insights, let’s dive even deeper and bring your ESG analytics to the next level. This comes down to data enrichment: the addition of advanced third-party datasets to your internal business data to heighten your insights. What’s the need for this in practice?Take compliance, for instance. Increasingly strict ESG legislative requirements mean more reporting on the potential impacts of climate change on your organization. Without enrichment, you’ll have limited insight into environmental factors – making it difficult for analyzation.

But supplementing your internal data with dynamic risk datasets is a different story – granting insight into the likelihood of wildfires, flooding, earthquakes, and other impactful weather events.

With this powerful big picture understanding, you’re able to better manage risk and confidently make decisions that are faster and more informed.

The same goes for social programs. Perhaps you want a more thorough understanding of demographic trends and historical patterns. Demographic datasets help you understand not only the places where people live, work, and do business – but also where there are opportunities to support underserved communities and populations.

To gain more accuracy in your environmental, social, and governance risk and analytics metrics, data enrichment is needed to complete the picture.