One of the biggest challenges in conducting Life Cycle Assessment (LCA), in both industry and academia, is access to primary data. It's widely accepted that the most reliable, representative LCAs are built on primary data (i.e. data that is specific to the system being assessed).
It is also clear that it no person or company can realistically investigate and audit up and down their entire supply chain - from the fuel composition and emissions of their electricity supplier, to the exact fertiliser quantities used on a tomato farm that supplies tomatoes to their sauce manufacturer, or the emissions at the facilities where their product's packaging is incinerated. This is why secondary databases with averaged values exist. They offer reliable, credible datasets, often differentiated by geographical locations or technologies applied.
In an ideal world, every actor in the value chain would model their activities and make the data accessible to anyone up or downstream.
In reality, some suppliers measure some of the activities and provide some of the impacts. Companies often hold structured data on parts of their own resource use. For example, partial greenhouse gas accounting is now fairly common, but many other emissions and environmental impacts are still unknown. These gaps then have to be filled with secondary data or assumptions and defaults.
Sustained supports companies in finding the right balance. Our platform fills data gaps with high-quality defaults and enables continuous improvement as more specific, primary data becomes available.
So, how much primary data is “enough”? At what point along this gradient does an LCA become meaningful? The answer depends on your goal. Whether you’re looking to make product design decisions, develop your reduction roadmap or report on your impact, you can take a different approach.
If your objective is to identify environmental hotspots across your product portfolio, so you can prioritise focus areas, then secondary data is a good starting point.
In Sustained, you can run a screening LCA using your basic product information. We apply the appropriate datasets and default values across processing, distribution, consumption and End-of-Life (EoL) stages. While this is not suitable for a published study or external claims, this gives you early, directional insight into your highest impact ingredients or components, and where to focus your efforts.
We also offer a Recipe Formulation tool - it lets you evaluate products based solely on ingredients, ideal for food businesses where most product impact comes from ingredients. This is particularly helpful for chefs or downstream partners, who aren’t responsible for sourcing but want to make lower impact choices in their dishes.
Once you’ve identified key hotspots, you can start improving data quality, starting with the data you already control by updating your model with first party data ((in other words, the minimum activity data you need to qualify as a screening LCA). For example:
This produces a more accurate, decision-grade footprint and opens the door to credible claims about your production impact.
The next step is to work with suppliers, especially those providing high impact inputs. If they already have their own assessments, you can override the secondary datasets used with supplier specific data. If not, Sustained can help them build their own models, which can be directly linked with your own in your Sustained workspace.
For external reporting, data quality becomes critical. Most standards set minimum thresholds for primary data, especially for impacts that contribute significantly to the overall footprint.
Frameworks like the EU’s Product Environmental Footprint (PEF) require a Data Quality Requirement (DQR) which considers:
To pass these standards, you’ll need a high proportion of verified primary data, from your own operations and your suppliers.
Like our previous posts on system boundaries and allocation, this article breaks down another LCA concept into practical, manageable steps. You don’t need perfect data to begin, you can gather valuable insights with the data you have today. Use defaults to screen, improve what you control, then work with your suppliers. Whether your goal is to design lower-impact products, track improvements, or prepare for credible reporting, the path forward is the same: Start with what you have. Improve what matters most. Keep going.