Once your initial calculation is complete, Pickler helps you continuously improve your results by reporting on the data quality of every product.
What is data quality?
In LCA, data quality reflects how specific and reliable your inputs are. It consists of three data types:
Primary data: Product-specific data that comes directly from your own operations or your suppliers (e.g., exact material weights, processing location, or energy use).
Secondary data: The use of IDEMAT data, when primary data isn’t available. Reliable, research-based impact values for materials, processes, transport, and energy.
Default values: Temporary, conservative assumptions provided by Pickler to keep calculations transparent and complete when neither primary nor secondary data is available yet.
Why would you improve data quality?
Better data makes your footprint more accurate, more credible, and more useful for real decision-making. You don’t need perfection — just steady improvement where it matters. Improving your data quality, results in to:
More accurate results – Calculations become product-specific instead of based on averages or defaults.
Clear improvement insights – You see which materials or processes drive impact and where to optimize.
Stronger claims & compliance – Verifiable data builds trust with customers, auditors, and regulators.
Often a lower footprint – Real supplier data can replace conservative defaults, reducing your results.
What to focus on?
Improving data quality doesn’t mean collecting perfect data. No major EU regulation requires 100% primary data — they expect transparent, verifiable inputs and allow secondary data when supplier data isn’t available.
Focus on becoming more accurate over time. Start with the data you have and improve it where it matters most, driven by high-volume products or customer requests. This keeps the work manageable and ensures your efforts actually reduce your footprint.
On the products over page in Pickler, you can filter on percentage primary, secondary and default data, and use it to decide what products to focus on.
Where to collect primary data
Primary data comes directly from your value chain, typically from:
Your own operations (weights, production steps, packaging configuration).
Suppliers (material specs, processing details, energy use).
Logistics partners (transport distances and modes).
In practice, most companies start by requesting data from tier-1 suppliers—the companies you buy products from. They usually have the information needed for meaningful improvements.
What data you can typically ask for
1. Material weights
Confirm exact weights in grams. Small weight differences can meaningfully change results.
2. Processing energy consumption
If available:
Electricity (kWh per product)
Heat (MJ per product)
3. Processing energy mix
Energy mix data from the processing location; for example the use of solar panels.
4. Transport distances & methods
Distance from supplier → your warehouse, plus mode (truck/ship).
Improving data quality gives you credibility, control and clarity—essential for reducing your footprint and proving it.