Beyond the Supply Chain: Why 'Complete' LCA Models Miss the Mark
"Rethinking environmental assessments for real-world impact"
Life Cycle Assessment (LCA) is a powerful tool for evaluating the environmental impacts of a product or service throughout its entire life cycle. Traditionally, process-based LCAs have been used, but they often face criticism for having 'incomplete' system boundaries. This has led to the development of hybrid LCAs, which combine process-based data with input-output (IO) models to capture a broader range of economic activities.
The core idea behind hybrid LCA is appealing: by including more and more processes, we can get closer to a truly 'complete' picture of environmental impacts. But is this pursuit of completeness actually worthwhile? Does adding every possible economic activity really improve the accuracy and relevance of our assessments? Some researchers are beginning to question whether expanding the system boundary is truly the key to better environmental decision-making.
This article unpacks the debate around system boundaries in LCA, exploring the limitations of both process-based and hybrid approaches. We'll delve into why the quest for 'completeness' might be a distraction from more critical issues, and how a more focused, market-aware approach can lead to more effective strategies for reducing environmental impact.
Why Completeness Matters
A complete life-cycle perspective is intended to reveal environmental impacts that may be missed when analysis focuses on manufacturing alone. However, the usefulness of any LCA depends on the quality of its data, system boundaries, and methodological choices. Results should therefore be interpreted as structured estimates rather than perfectly comprehensive accounts.
The Full Life-Cycle Method
Life cycle assessment evaluates environmental impacts across a product's entire life cycle, from raw-material extraction through manufacturing, use, disposal, or recycling. This broader scope is a strength because manufacturing alone may omit important impacts elsewhere in the system. At the same time, LCA faces data-quality limitations, differences in system-boundary definitions, methodological inconsistencies, uncertainty, incomplete impact coverage, and subjectivity in modeling choices. These constraints can affect both accuracy and the applicability of results to decision-making.
From Concept to Standardization
LCA is a methodology for assessing impacts associated with all stages of a commercial product, process, or service. Its history is commonly described as a progression from the 1970s to the present, including methodological development, practical application, international harmonization, standardization, and dissemination. A review of the field identifies five broad periods: the early years, conception, standardization, elaboration, and the concept period.
The Illusion of Completeness: Why More Isn't Always Better
The idea of a perfectly complete LCA model, one that accounts for every single economic activity on Earth, seems intuitively appealing. However, the practical value of such a model is questionable. The decisions LCA seeks to inform are usually about specific changes: altering a product system, promoting an alternative, or reducing impacts in a particular area. A model that includes everything may end up obscuring the relevant factors and providing little actionable insight.
- Narrow Focus: Concentrating solely on the supply chain can blind us to broader economic effects.
- Unrealistic Assumptions: Ignoring price signals and market constraints creates a distorted picture of reality.
- Doubling Down on Limitations: Hybrid LCA, by incorporating IO models, inadvertently reinforces these problematic assumptions.
Toward Dynamic and System-Level LCA
Recent LCA research is expanding beyond static product assessments. A 2026 scoping review examined dynamic LCA literature published between 2015 and 2025, focusing on sectoral applications, methodological implementation, digitalization, decision-support systems, and policy relevance. Another 2026 systematic review examined prospective process-based LCA for modeling future environmental impacts at national to global scales. Reviews published in 2026 also consider LCA's role as a catalyst for environmental change and identify methodological challenges and future directions for improved decision support.
The Limits Behind the Label
Critiques of LCA emphasize that the method has inherent boundaries and constraints that must be acknowledged for responsible use. Reported challenges include data-quality limitations, variation in system-boundary definitions, and methodological inconsistencies. These weaknesses do not make LCA useless, but they can limit how confidently results are compared or applied to sustainability decisions.
Comparing Results Carefully
Comparisons between LCA results are most informative when the studies use compatible boundaries, data, and modeling choices. Differences in those choices can change which impacts are included and how alternatives appear relative to one another. LCA comparisons should therefore be treated as context-dependent evidence rather than universally transferable rankings.
Reimagining LCA: Flexibility and Market Awareness
Future LCA studies should shift away from simply 'completing' the system boundary within a conventional supply chain and linear framework. A move towards more realistic modeling of our complicated human-environment system is important. Instead of trying to include everything, the study argues for flexible, market-based system boundaries tailored to the specific decision at hand. This involves considering the scale of potential changes and how they may affect the economy. A change at larger scales is likely to have a broader impact, thus justifying a broader system boundary, while a broad system boundary for a small change will likely result in overestimates. Ultimately, more is not necessarily better when it comes to LCA.
From Product Scores to Strategy
Research on life cycle sustainability assessment has broadened the vocabulary used to capture sustainability performance, including life cycle sustainability performance, analysis, and evaluation. This wider framing reflects an effort to assess sustainability across more than a narrowly defined environmental result. In practice, Anthesis applies life-cycle assessment at industry level through business groups and consortia, using sector-wide measurements as a benchmark and evidence base for sustainability strategies and reduction targets.
Machine Learning Enters the Workflow
Machine learning is emerging as a possible way to strengthen all four LCA phases: goal and scope, life cycle inventory, life cycle impact assessment, and interpretation. A 2025 review maps recent research in this area through a reproducible bibliometric analysis. Industry discussions in 2026 also identify new trends intended to simplify footprint tracking and support organizations pursuing sustainability goals.
Beyond Environmental Metrics
A broader sustainability framework evaluates environmental, economic, and social impacts of products and services together. This approach is presented as a more complete picture than examining environmental effects alone. At the same time, digital tools and artificial intelligence are making LCA more practical for everyday business use.
LCA in Practice
Real-world applications show LCA being used across transport, construction, materials, and digital infrastructure. One openLCA case study evaluates the environmental impact of introducing Longer and Heavier Vehicles in Germany, including vehicles measuring up to 25.25 meters and weighing up to 60 tons. Another case-study source examines recycled aggregates for concrete production and digital infrastructure, while the FNR highlights 25 examples of research with impact involving materials, products, technologies, and policies.