Why primary data matters
Primary data is the difference between a footprint that describes your product and one that describes an industry average that may look nothing like it. Two facilities making the same material can have very different footprints depending on their energy source, process route, and location. Generic data erases those differences; primary data captures them.
This matters most where the impact is concentrated. In battery and minerals supply chains, a small number of energy-intensive steps such as refining, conversion, and cell manufacturing usually dominate the total footprint. Using primary data for those steps is what makes the result both accurate and defensible. Using a generic proxy there can move the answer dramatically.
Primary data and the Data Quality Rating
Primary data is also how a footprint achieves a compliant Data Quality Rating (DQR). Because the DQR scores datasets on technological, geographical, and time-related representativeness, site-specific primary data scores well: it reflects the actual technology, location, and time period. A generic database entry from another region or an older year scores poorly. PEF category rules typically require high-quality data for the most relevant processes, which in practice means primary data for the hotspots.
Primary versus secondary data
A well-built LCA uses both, deliberately. Primary data is gathered for the foreground system, the processes the company runs or can influence, and the ones that dominate the impact. Secondary data from quality background databases such as ecoinvent is used for upstream processes that are minor contributors or impractical to measure directly. The skill is knowing where primary data is essential and where secondary data is acceptable, and documenting both honestly.
Why primary data is hard, and valuable
Collecting primary data across a multi-tier supply chain is the hardest part of most industrial LCAs. Suppliers may be reluctant to share, data may be inconsistent, and tier-2 and tier-3 visibility is limited. That difficulty is exactly why primary data is valuable: a footprint built on it is far harder to challenge, and far more useful for a customer or regulator who needs to trust the number.
Minviro's approach is built on primary supply chain data, including the XYCLE Battery Materials Database covering more than 70% of global battery materials. See how Minviro sources primary data →
Why primary data matters
Primary data is the difference between a footprint that describes your product and one that describes an industry average that may look nothing like it. Two facilities making the same material can have very different footprints depending on their energy source, process route, and location. Generic data erases those differences; primary data captures them.
This matters most where the impact is concentrated. In battery and minerals supply chains, a small number of energy-intensive steps such as refining, conversion, and cell manufacturing usually dominate the total footprint. Using primary data for those steps is what makes the result both accurate and defensible. Using a generic proxy there can move the answer dramatically.
Primary data and the Data Quality Rating
Primary data is also how a footprint achieves a compliant Data Quality Rating (DQR). Because the DQR scores datasets on technological, geographical, and time-related representativeness, site-specific primary data scores well: it reflects the actual technology, location, and time period. A generic database entry from another region or an older year scores poorly. PEF category rules typically require high-quality data for the most relevant processes, which in practice means primary data for the hotspots.
Primary versus secondary data
A well-built LCA uses both, deliberately. Primary data is gathered for the foreground system, the processes the company runs or can influence, and the ones that dominate the impact. Secondary data from quality background databases such as ecoinvent is used for upstream processes that are minor contributors or impractical to measure directly. The skill is knowing where primary data is essential and where secondary data is acceptable, and documenting both honestly.
Why primary data is hard, and valuable
Collecting primary data across a multi-tier supply chain is the hardest part of most industrial LCAs. Suppliers may be reluctant to share, data may be inconsistent, and tier-2 and tier-3 visibility is limited. That difficulty is exactly why primary data is valuable: a footprint built on it is far harder to challenge, and far more useful for a customer or regulator who needs to trust the number.
Minviro's approach is built on primary supply chain data, including the XYCLE Battery Materials Database covering more than 70% of global battery materials. See how Minviro sources primary data →
Why primary data matters
Primary data is the difference between a footprint that describes your product and one that describes an industry average that may look nothing like it. Two facilities making the same material can have very different footprints depending on their energy source, process route, and location. Generic data erases those differences; primary data captures them.
This matters most where the impact is concentrated. In battery and minerals supply chains, a small number of energy-intensive steps such as refining, conversion, and cell manufacturing usually dominate the total footprint. Using primary data for those steps is what makes the result both accurate and defensible. Using a generic proxy there can move the answer dramatically.
Primary data and the Data Quality Rating
Primary data is also how a footprint achieves a compliant Data Quality Rating (DQR). Because the DQR scores datasets on technological, geographical, and time-related representativeness, site-specific primary data scores well: it reflects the actual technology, location, and time period. A generic database entry from another region or an older year scores poorly. PEF category rules typically require high-quality data for the most relevant processes, which in practice means primary data for the hotspots.
Primary versus secondary data
A well-built LCA uses both, deliberately. Primary data is gathered for the foreground system, the processes the company runs or can influence, and the ones that dominate the impact. Secondary data from quality background databases such as ecoinvent is used for upstream processes that are minor contributors or impractical to measure directly. The skill is knowing where primary data is essential and where secondary data is acceptable, and documenting both honestly.
Why primary data is hard, and valuable
Collecting primary data across a multi-tier supply chain is the hardest part of most industrial LCAs. Suppliers may be reluctant to share, data may be inconsistent, and tier-2 and tier-3 visibility is limited. That difficulty is exactly why primary data is valuable: a footprint built on it is far harder to challenge, and far more useful for a customer or regulator who needs to trust the number.
Minviro's approach is built on primary supply chain data, including the XYCLE Battery Materials Database covering more than 70% of global battery materials. See how Minviro sources primary data →