A Lasting Data Foundation for Environmental Reporting
Wednesday, 26 August 2026
16:00 CEST
What‘s this webinar about?
Building a reliable, future-proof data foundation for environmental assessments is a strategic priority for companies across the chemical value chain. But when building life cycle inventories (LCIs), teams often face a data challenge across three dimensions:
Incomplete coverage: Limited data availability forces teams to rely on self-built proxies, creating structural blind spots that can hide relevant hotspots in environmental assessments.
Methodological inconsistency: Even when calculations are fully ISO-compliant, differences in system boundaries, allocation methods, or background data can make results impossible to compare across suppliers, products, or portfolios.
Limited actionability: Generic market averages hide the variability of technologies, feedstocks, suppliers, and regions, making real hotspots and lower-impact pathways difficult to identify.
In this webinar, we will show how to overcome these three dimensions of the data challenge.
You will learn how to build a future-proof data foundation with a maintenance workflow that goes beyond this year’s reporting and creates a reliable basis for the years to come. It ensures reliable updates and long-term maintainability, high data coverage through quality-assured approaches to closing data gaps, and year-to-year change logs and progress tracking. This foundation will allow you to report with confidence, identify improvement levers, and answer even the toughest customer questions.
Join us to learn how to keep your environmental assessment data credible, comparable and ready for real-world decision-making.
Agenda
The Challenges of Life Cycle Data Today
From One-Off Reporting to Reliable Progress Tracking
The Way Forward:
Building a Future-Proof Data Foundation
Live Q&A
With the participation of
Guy Kobani
Global Sales Manager
Ludwig Jolmes
SUSTAINABILITY EXPERT FOR CHEMICAL SUPPLY CHAINS
Arne Kteälhön
Managing Director & Co-Founder
Learn how to solve the three dimensions of your data challenge.