Best practices on adding product data

In Pickler, transport represents the movement from the processing gate (production) to a warehouse. If that warehouse is your own distribution center, you model transport up to that point. If your “warehouse” is actually your customer who resells the product, then transport effectively goes from production to each customer location.

Following pure LCA logic, each different destination would mean a slightly different lifecycle. So yes — ideally, you would create a unique product variation for every destination.

However, in practice, this quickly becomes unmanageable. Creating dozens of nearly identical products usually doesn’t improve your insights enough to justify the added complexity.

You are free to model it this way, but a more practical approach is to simplify where possible. If the product itself is the same and only the destination differs, you can work with one product (or a few key variations) and define a representative transport scenario.

This aligns with LCA best practice: model the lifecycle as accurately as needed for decision-making, while keeping the model scalable and maintainable.

For example, if most of your volume goes to customers in the Netherlands, you could model transport to a typical Dutch warehouse or customer as your main scenario. Even if some shipments go elsewhere, this still represents your overall flow well and is easy to justify based on your logistics data.

As long as your model reflects your supply chain realistically and you can explain your assumptions, you’re doing it right.

In theory, yes — if you follow pure LCA logic, each country can have a different waste treatment system, which means a slightly different lifecycle per destination.

However, in practice, you don’t need to create a separate product for every country.

If the differences in end-of-life between countries are relatively small (which is often the case within regions like Europe), you can decide to model them together in one product. Instead of duplicating SKUs, you reflect this using a distribution across end-of-life regions.

This means you assign percentages based on where your products are actually disposed of.

For example, if most of your products are sold in the Netherlands and the rest across Europe, you could model:

This captures the real-world flow of your products without adding unnecessary complexity.

Only if differences between regions are significant and relevant for your decisions, it makes sense to model them separately.

This aligns with LCA best practice: focus on differences that materially impact results, and simplify where they don’t.

You don’t need exact precision per country. It’s perfectly acceptable to:

As long as your setup reflects reality reasonably well and you can explain your assumptions, you’re doing it right.