The Process of Collecting Data

Module 3 highlights strategies for collecting business data from internal and external upstream and downstream stakeholders. We will cover the importance of having complete and accurate data. In this module, you will:

• Gain a high-level understanding of data collection strategies
• Learn how to work with your value chain to gather the most granular data for emissions estimates
• Understand how organizations can automate the data collection process through software

Estimated time to complete is20 min.

Terms to Know

• Product GHG Inventory - A Product GHG Inventory measures the total GHG emissions generated by a specific product, from the extraction of raw materials used in that product to the product's end-of-life use. For example, a particular toothbrush model's total GHG emissions from cradle to grave.  
• Climate Management and Accounting Platform—Climate Management and Accounting Platforms (CMAPs) have been developed as cutting-edge modern tools for performing carbon accounting in a completely software-based environment. CMAP companies can deliver substantially more efficient and cost-effective carbon accounting through a Software-as-a-service model, with an interface anyone can use without needing previous carbon accounting experience.

The Process of Collecting Data

When collecting scope 3 data, engaging and working with internal and external partners, such as procurement, operations, logistics, audit, and IT teams, is crucial.

Prioritize Data Collection Efforts

Because Scope 3 emissions can span dozens of activities and hundreds of suppliers, organizations should avoid attempting to collect highly detailed data for all categories at once. Instead, the GHG Protocol recommends prioritizing data collection efforts based on a combination of materiality, feasibility, and strategic relevance.

Organizations should prioritize Scope 3 data collection using the following criteria:

• GHG significance
  Focus first on Scope 3 activities that contribute the largest share of total emissions. These categories are most likely to influence overall footprint accuracy and reduction outcomes.
• Reduction opportunities
  Prioritize activities where improved data can support meaningful emissions reductions, such as supplier manufacturing processes, logistics, or product use.
• Business goal alignment
  Align data collection with broader organizational goals, such as regulatory compliance, science-based target setting, customer disclosure requirements, or procurement strategy.

This prioritization helps organizations focus effort where better data will deliver the greatest value, rather than spreading resources thin across less material activities.

Select Data

Once priority Scope 3 categories and activities are identified, organizations determine which types of data are available and appropriate to use. The GHG Protocol distinguishes between two primary data types:

• Primary data
  Data from specific activities or suppliers within an organization’s value chain. Examples include supplier-reported energy use, site-specific emissions, product-level inventories, or measured activity data.
• Secondary data
  Emissions data derived from industry averages, proxy datasets, or third-party databases that are not specific to an individual supplier or activity. Secondary data is often combined with activity data—such as spend, distance, or quantities purchased—to estimate emissions.

Organizations commonly use a mix of primary and secondary data, starting with what is readily available and increasing data specificity over time.
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We’ll explore these data types in more detail in the next lesson.

Collect Data and Fill Gaps

After selecting data types, organizations begin collecting information from internal systems and external partners.

Primary data may be obtained through:

• Supplier-provided emissions or activity data
• Utility bills, meter readings, or fuel records
• Purchase records and production data
• Engineering models, mass balance calculations, or direct monitoring (where applicable)

For priority Scope 3 categories, organizations often engage suppliers and other value-chain partners to request site-specific or activity-specific data, improving accuracy and traceability.

Where primary data is unavailable or incomplete, organizations should use secondary data to fill gaps. When selecting secondary data sources, best practice is to prioritize:

• Peer-reviewed databases
• Widely recognized industry datasets
• Emission factor sets published by national governments or reputable research institutions

Using consistent and transparent secondary data sources ensures that estimates are defensible and comparable across reporting periods.

Improve Data Quality Over Time

Scope 3 data collection is inherently iterative. Organizations are not expected to have perfect data in the first year of reporting. Instead, they should continuously assess and improve data quality as systems, supplier engagement, and internal processes mature.

Organizations can evaluate data quality both:

• At the point of data selection, by considering factors such as data specificity, completeness, and reliability
• After inventory compilation, by reviewing which data sources most influenced overall emissions results

To maximize impact, organizations should prioritize data quality improvements for activities that are both:

• High emissions, and
• Low data quality

Focusing improvement efforts on these areas helps organizations progressively replace estimates with more accurate, supplier-specific data, strengthening the credibility and usefulness of their Scope 3 inventory over time.

Lesson takeaway

Effective Scope 3 data collection requires prioritization, flexibility, and continuous improvement. By focusing on the most material emissions sources, using a mix of primary and secondary data, and improving data quality over time, organizations can build a Scope 3 inventory that is both practical and decision-useful.