Most errors arise not from bad intentions, but from unclear definitions, inconsistent data handling, or missing documentation. The good news: nearly all of them are easy to fix once you know what to look for. This guide breaks down the ten most common LCA mistakes—and how transparent AI, structured workflows, and centralized data in Sustainly help beginners and small teams avoid them from day one.
1) Vague or Shifting Functional Unit
The functional unit is the anchor of your assessment. When it’s unclear or changes halfway through the project, everything becomes inconsistent. Fix: Define a precise, measurable functional unit and keep it constant across all scenarios.In Sustainly: it’s stored in your project settings and reused automatically.
A stable functional unit is the easiest way to build credibility in sustainability analysis.
2) System Boundaries That Don’t Match the Goal
Boundaries define how much of the product lifecycle you’re analyzing.Unclear choices make results hard to interpret. Fix: Choose boundaries aligned with your goal (e.g., cradle-to-gate or cradle-to-grave) and document what’s included or excluded.
In Sustainly: boundaries stay visible throughout your model, keeping teams aligned.
3) Mixing Data Without Tracking Sources
Beginners often blend spreadsheet values, supplier information, and old assumptions without tagging sources. Fix: Record the year, source, and quality of each input.In Sustainly: you can attach metadata directly to each flow, helping maintain traceability across products and versions.
4) Selecting Background Data That Doesn’t Match Your Context
Choosing datasets from the wrong region or technology can shift results dramatically. Fix: Filter by geography, production pathway, and reference year.In Sustainly: AI-guided dataset suggestions help beginners choose the most relevant option.
5) Unit Conversions Gone Wrong
Unit errors are one of the most common LCA issues—grams vs. kilograms, MJ vs. kWh, CO₂ vs. CO₂e. Fix: Convert all data into consistent units before modeling.In Sustainly: automated unit harmonization prevents mismatches.
6) Confusing Allocation Choices
Allocation decides how shared processes or recycled content are handled.Changing methods without realizing it breaks comparability. Fix: Pick one method and use it consistently across your model.
In Sustainly: allocation is defined at project level to keep workflows aligned.
7) Only Reporting Carbon Footprint
Carbon results are useful, but focusing on climate alone may miss impacts related to water, toxicity, or resources. Fix: Include at least one broader category to show balanced insight.In Sustainly: switching between climate-only and multi-category views is one click.
Data-driven sustainability means understanding trade-offs—not just CO₂.
8) No Scenario Analysis
Without alternatives, an LCA becomes a static report instead of a decision tool. Fix: Create 2–4 realistic scenarios using the same functional unit and boundaries.In Sustainly: you can clone the baseline and explore improvements in minutes.
9) Weak or Missing Interpretation
Numbers alone don’t help teams make better decisions.Interpretation should highlight hotspots, assumptions, and clear next steps. Fix: Summarize the biggest drivers, identify uncertainties, and propose one actionable improvement.
In Sustainly: hotspot charts and notes panels make this step easier for beginners and non-experts.
10) Skipping Structured Outputs (When You Need Them)
If you’re preparing claims for customers or internal reviews, results need structure and clarity. Fix: Follow relevant communication frameworks and document assumptions clearly.In Sustainly: EPD-style modules help generate verifier-ready structures without requiring advanced expertise.
Quick Validation Checklist
- Functional unit fixed
- Boundaries clearly defined
- Data sources documented
- Relevant background datasets selected
- Units consistent
- Allocation method stable
- Climate + additional categories considered
- Scenarios included
- Interpretation and uncertainties documented
- Structured communication when needed
FAQ
Is a screening LCA acceptable for early decisions?Yes—just be clear about assumptions and note any limitations. Which datasets should beginners start with?
Use broad, vetted regional datasets first; refine later if needed. Can teams collaborate easily?
Sustainly’s shared workspace and centralized sustainability data help teams stay aligned as models evolve.