Semarchy: Turning ESG Data Into Actionable Insights

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Hervé Chapron, SVP & General EMEA, Semarchy
Hervé Chapron, SVP & General EMEA, Semarchy explains how manufacturers can best navigate ESG data to meet regulatory requirements and enhance operations

Hervé Chapron, SVP & General EMEA at Semarchy, shares a nuanced approach to navigating ESG data to meet stricter regulatory requirements with Manufacturing Digital.

How can manufacturers turn ESG data into actionable insights?

Since 2021, there has been a significant rise in companies setting ESG targets. According to the ESG in Manufacturing report by Make UK and Lloyds Bank, approximately 62% of manufacturers have committed to these sustainability goals, driven by pressure from labour markets, government, investors and customers. However, unlike other sectors, manufacturers must manage intricate data while often lacking the necessary systems to swiftly adapt to evolving reporting standards.

Master data management (MDM) and continuous data governance become crucial at this point. They provide a framework for maintaining a consistent, unified view of data. Just as you wouldn’t report financial data without ensuring its accuracy, it’s equally important to address ESG data with the same level of rigour.

When equipped with the right tools, manufacturers can use their data to tackle crucial ESG requirements and seize opportunities in this space as it grows.

How can manufacturers use data systems for effective risk identification and mitigation?

With accurate data, manufacturers can gain insights into operational efficiency and regulatory compliance. MDM supports this by breaking down data silos, which enhances visibility and traceability across the entire supply chain. This approach allows manufacturers to access informative data covering the entire product lifecycle: from raw materials to final products and customer feedback.

Furthermore, effective risk management must encompass the supply chain to tackle sustainability issues and prevent disruptions. Mastering data related to third-party relationships is crucial, as it allows manufacturers to monitor supplier and vendor activities. 

It also helps identify ESG risks like unethical sourcing practices, labour violations or environmental non-compliance that impact Scope 3 emissions. By integrating this information, manufacturers can enhance their practices throughout the product lifecycle, ultimately delivering better customer experiences.

How can you leverage this data to comply with stringent ESG standards?

Securing the support of investors and consumers depends on adhering to regulatory frameworks such as the International Financial Reporting Standards (IFRS) and Sustainability Accounting Standards Board (SASB). Environmental reporting further complicates this task, requiring manufacturers to gather and disclose transparent, verifiable data.

MDM is invaluable in this context, as it ensures data integrity and consistency by consolidating information from diverse sources and aligning it with the relevant reporting requirements. An MDM framework enables organisations to establish clear data quality rules, validate data against predefined criteria and efficiently identify and resolve inconsistencies.

Implementing MDM allows organisations to centralise and govern their ESG data effectively, creating a single, reliable source of truth. This approach not only streamlines reporting processes but also enhances the credibility of ESG disclosures, building greater trust among stakeholders.

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How can you use these data insights to drive ESG initiatives forward? 

Turning ESG initiatives from theory into practice depends significantly on data insights. By merging financial and ESG datasets in a data lake, organisations can conduct more comprehensive analytics, uncovering insights that provide dual benefits. 

These insights improve a company’s profitability by pinpointing areas of waste and inefficiency across operations. For instance, analysing energy usage patterns might uncover opportunities to reduce consumption, resulting in cost savings and lower emissions. 

At the same time, detailed ESG data analysis enables businesses to better quantify and communicate their sustainability efforts. This transparency and commitment can boost appeal to socially conscious consumers and investors.

What is the best practice for manufacturers to create a solid data foundation?

To support ESG efforts effectively with robust data, manufacturers should adhere to the following best practices:

First, conduct a comprehensive ESG data audit to identify gaps in your current data collection and management processes. Next, implement a centralised ESG data hub based on MDM principles, which can be integrated with existing systems and offer real-time reporting capabilities.

Develop a clear data governance framework tailored specifically for ESG metrics, including data quality standards, roles and responsibilities and verification processes. Invest in training programmes to ensure all relevant staff understand ESG data requirements and can contribute to accurate data collection and reporting.

Finally, benchmark your ESG data management practices regularly against industry leaders and update your systems and processes as needed.

The strategic importance of ESG data management for manufacturers

In conclusion, mastering ESG data management goes beyond mere compliance; it is an essential strategy for transforming ambitious sustainability goals into effective, actionable practices. By ensuring data accuracy and consistency, manufacturers can seamlessly align their operations with ESG principles, fostering a culture rooted in transparency and accountability.

This approach not only meets reporting demands but also positions manufacturers to excel in a marketplace increasingly focused on sustainability. Now is the time to develop robust ESG strategies and lead in sustainable practices before it's too late.

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