Life Cycle Assessment (LCA) can be a powerful tool in product sustainability strategies, but its implementation often poses major challenges for manufacturing companies. A central difficulty lies in collecting high-quality primary data for the Life Cycle Inventory (LCI), including data on energy demand in production processes. Existing company data infrastructures frequently restrict the availability and granularity of such information, limiting the robustness of product environmental sustainability assessments. This paper introduces a practical, standards-aligned decision tree that supports companies in acquiring and applying primary LCI data on production energy demand. The methodology translates requirements from recognized standards and frameworks into actionable steps, providing clear pathways and tailored recommendations for different operational situations. By doing so, it enables organizations to balance methodological accuracy with feasibility in industrial practice and to progressively strengthen their data collection systems. An industrial use case from the plastics sector demonstrates how the approach can be applied to capture and process energy demand data while also guiding targeted improvements to data infrastructures. The decision tree thus serves both as an immediate aid for selecting appropriate data strategies and as a longer-term roadmap for enhancing LCI data quality. Adaptable across diverse manufacturing contexts, the methodology outlines a practical pathway for achieving more reliable energy-related primary data under real-world conditions. Download: Download spreadsheet (14KB)
Pohler et al. (Thu,) studied this question.