4 Data Management Best Practices for Industrial Decarbonization

Contributed by: Devin Partida

How do industrial facilities decarbonize without knowing where the problem lies? Even with reliable information on carbon dioxide emissions, how can industries convert raw data points into actionable insights? Data management is key to emissions reduction and stakeholders in the energy industry can only maximize their strategy’s effectiveness by integrating best practices into operational strategies.

Leveraging Data for Industrial Decarbonization
Industrial operations have consistently been among the top greenhouse gas emitters for decades. Industries - which include steel, cement, and chemical production, as well as oil, gas, and coal extraction - account for 30% of carbon dioxide emissions globally. As regulations tighten and consumer expectations shift, industries are increasingly shifting their focus towards effective decarbonization.

Data management is fundamental to driving decarbonization efforts within industrial operations. However, business leaders must first understand how to effectively source, analyze, and utilize it - only then can they grasp how to transform raw data points into actionable insights.

While whitepapers, public reports, and government statistical offices exist, relevant, high-quality information is rare. For example, while research shows industry produces 528 million tons of carbon dioxide equivalent emissions annually, specifics are unavailable. Facilities must know how region, vendor selection, sector, and product type factor into direct and indirect emissions.

The Importance of a Robust Data Infrastructure
Relying on disparate sources for accurate, up-to-date information is nonsensical at best. Industry leaders must leverage digitalization to gather information from the source. An effective decarbonization strategy should involve a robust data infrastructure and tracking tools for carbon dioxide emissions.

Real-time monitoring and reporting are essential for maintaining insight accuracy. Moreover, they help decision-makers identify data discrepancies and potential process improvements, enabling timely intervention.

According to one report, just 49% of executives felt their organizations were somewhat or very effective at utilizing information to drive strategies. The only way for them to develop effective decarbonization plans is to manage what they source, store, analyze, and use.

READ: Seneca Resources’ Strategy for Regulatory and Voluntary Compliance

4 Data Management Best Practices for Decarbonization
Here are the top data management best practices to ensure the highest chance of success:

1. Assign Ownership of Data
Too few people take data security seriously. In 2023, just 13% of the global population protected their information. Energy companies must establish governance roles to secure their datasets. This includes assigning roles to executives, information technology team members, and vendors.

2. Centralize Storage Systems
Cloud computing offers on-demand access to information regardless of location. While the perks of a centralized server are convenient, the real benefit is standardization - eliminating silos and hardware incompatibilities to coordinate comprehensive decarbonization efforts.

3. Develop Archival Requirements
Energy organizations should establish an audit trail to manage access and utilization of archival information - data collected in the past that is not actively being analyzed or used. This approach is ideal for regulatory compliance and making referencing seamless.

4. Standardize Data Procedures
Industrial facilities must standardize emissions data. This process involves cleaning and transforming information to keep insights accurate and relevant. On a broader scale, it applies to departments and locations, ensuring findings are shareable.

Consider Digitalization to Improve Data Management
Industrial facilities can use advanced analytics tools to optimize processes involving data, accelerating their progress toward sustainability goals. Artificial intelligence is among the leading options because of its versatility. Moreover, its market size is expanding - experts expect it will reach $826.73 billion by 2030, up 786% from 2020 - so many solutions exist.

Advanced analytics technologies like AI can act autonomously and react to unplanned events, so professionals need not worry when their tools go without oversight for extended periods. Reports will remain accurate and management practices will stay compliant.

AI offers automation and around-the-clock analysis while requiring minimal human involvement. Additionally, it can uncover hidden patterns and extract precise insights from ambiguous information. On the administrative side, it can support data management by facilitating record retrieval or summarizing lengthy reports on demand.

Following Best Practices for Decarbonization
While best practices are generally considered industry standard procedures, they are relatively broad. Energy professionals should align them with their organization’s capabilities and goals to maximize their positive impact on industrial decarbonization efforts.

LISTEN: Episode 13: How Oil and Gas Companies Can Operationalize GHG Emissions Tracking

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