In supply chains, primary data is the raw data collected directly from sources, such as suppliers, manufacturers, or vendors. It provides businesses with insight into their production ecosystem. Secondary data, on the other hand, relies on industry averages, which are often not accurate. As defined by the Greenhouse Gas (GHG) Protocol, Scope 3 emissions refer to indirect emissions across a company’s supply chain. When the data used to calculate these emissions is inaccurate, it often leads to misinformed decisions. Choosing primary data improves accuracy and leads to better decision-making.
Since secondary data is fast and easily accessible, most companies prefer it to measure their supply chain emissions. However, the difference between secondary data and primary data is not just technical- it directly impacts the accuracy and reliability of business decisions.
The Role of Secondary Data: Useful, but Limited
Spend-based data calculates emissions using purchasing data and industry averages, rather than activity-based data that calculates emissions using actual operational parameters.
And secondary data uses spend-based emissions as it helps with early Scope 3 reporting, gives an approximate estimate if the supplier data is missing, and aligns with baseline GHG Protocol.
However, it comes with assumptions, such as:
• All suppliers behave like industry averages
• Energy sources are treated the same
• Logistics follow the same method
And these assumptions rarely reflect real-world operations.
Why Primary Data Matters
In supply chain emissions, primary data is activity-based data collected directly from suppliers and logistics. It includes:
- energy consumption by suppliers
- transport modes and distances
- emissions at various production levels
This leads to more accurate emissions data and reliable insights, enabling informed decision-making and not just reporting. A study published in Nature highlights that emissions estimates based on generic data can carry significant uncertainty, reinforcing the need for more precise, activity-based inputs.
The Core Challenge: Scope 3 Data Quality
Scope 3 emissions are the largest as they span across a product’s entire value chain, from production to use, transport, and end-of-life, yet they are the most inaccurate. The data often depends on estimates, assumptions, and incomplete supplier information. Research conducted by ScienceDirect shows that using assumptions in emissions modeling can lead to major inaccuracies.
For example, two suppliers may look the same using secondary data, but primary data often reveals the difference in their emissions. And this impacts decision-making.
When to Move Beyond Averages
Industry averages or secondary data can serve as a starting point, but not a long-term solution. As businesses start to move from reporting to reduction, secondary data begins to limit the accuracy and effectiveness of their decisions.
Shifting to primary data becomes important when:
• Emissions data is used to make business decisions
• Companies set reduction goals
• Supplier engagement becomes important
• External scrutiny increases
At this stage, averages pose a risk rather than an advantage.
Conclusion
The shift from secondary to primary data isn’t about perfection, but about reliable, decision-grade data.
As companies move from reporting to action, data quality becomes critical to both emissions reduction and cost optimization.
Fitsol supports this transition by enabling supplier-level primary data collection and aligning with GHG Protocol standards. Moving from spend-based to activity-based data improves accuracy and leads to better decisions.
Because better data doesn’t just measure emissions, it drives better outcomes.
FAQs
1. What is the difference between primary and secondary data in supply chain emissions?
Primary data is collected directly from suppliers, manufacturers, and logistics partners, reflecting actual operations. Secondary data relies on industry averages and estimates, which may not capture real-world variations. This difference directly impacts the accuracy of Scope 3 emissions calculations.
2. Why is secondary data unreliable for Scope 3 emissions reporting?
Secondary data is based on assumptions such as uniform supplier behavior, energy use, and logistics patterns. In reality, supply chains vary significantly, which makes these estimates less reliable. This can lead to inaccurate emissions reporting and limit the effectiveness of reduction strategies.
3. How does primary data improve emissions factor accuracy?
Primary data uses activity-based inputs like supplier energy consumption, transport modes, and production-level emissions. This improves emissions factor accuracy by reflecting real operational conditions, enabling companies to make more informed decisions and target emissions reduction efforts effectively.