From Requests to Reliable Datasets: Practical Approaches for Gathering Life Cycle Inventory (LCI) Data

Main Presenter:    Anna Ossolińska-Baldach 

Co-Authors:                                                  

High-quality life cycle inventory (LCI) data is a prerequisite for robust life cycle assessment (LCA), dataset development, and life cycle-based decision-making, particularly when working with sector groups, industry associations, and other collective industry initiatives. However, collecting LCI data from industry is often constrained by confidentiality concerns, limited internal resources, and inconsistent data formats across companies and regions. As a result, standardized “one-size-fits-all” data requests often lead to incomplete, non-comparable, or unusable datasets. Advancing life cycle innovation therefore requires flexible approaches that enable data collection under real-world conditions while maintaining consistency and representativeness.

This contribution shares lessons learned from LCI data collection in the chemical industry and addresses the following research question: How can practitioners move from initial data requests to reliable, representative datasets by adapting the collection approach to the stakeholder context? Using chemical production processes as an example, we propose a flexible framework that can be applied case-by-case depending on sector group structures, data maturity, and confidentiality requirements. Initial data are defined as mass and energy balances (MEBs) for specific production processes, providing a robust basis for iterative improvement and validation.

We describe two commonly observed collaboration pathways. First, validation by associations can accelerate participation, support harmonization, and reduce the reporting burden for individual companies. Second, company-level primary data collection enables higher granularity and improved representativeness where feasible, allowing for a better reflection of site- or technology-specific conditions.

Our findings show that successful LCI data collection depends less on choosing a single “best” method and more on selecting a pathway that fits the stakeholder context. Association-based approaches can enhance comparability and speed, while company-level collection can improve accuracy and detail. In practice, combining both pathways often provides the most robust outcome under varying levels of collaboration intensity and data availability.

The contribution offers a practical blueprint for transforming fragmented industrial inputs into reliable LCI datasets. While demonstrated with examples from the chemical industry, the approach is transferable to other sectors facing similar confidentiality constraints and heterogeneous production systems.

©2026 Forum for Sustainability through Life Cycle Innovation e.V. | Contact Us | Legal Info

CONTACT US

If you would like to get in touch with us, please feel free to send us a message. Thank you very much in advance.

Sending

Log in with your credentials

or    

Forgot your details?

Create Account