AI can clean and standardize this chaos in minutes — harmonizing names, mapping to the right datasets, and fixing units automatically so teams can focus on insight, not cleanup.
Sustainly’s transparent AI copilot makes taxonomy and unit harmonization fast, auditable, and scalable — keeping your sustainability data consistent across projects and teams.
What To Standardize
- Taxonomy: unify material and process names into canonical terms (e.g., “stainless steel 18/8”).
- Units: convert and align measurement systems (g→kg, miles→km, BTU→MJ, L→m³).
- Metadata: ensure regional, temporal, and technology qualifiers are properly defined.
- Sources: differentiate between primary, secondary, reported, or inferred data.
5-Step Harmonization Flow
- Collect datasets — from BOMs, utilities, transport, and packaging data.
- Detect conflicts — find duplicates, mixed units, or missing regional data.
- Suggest canonical terms — AI proposes matches, and you review or approve.
- Map to background datasets — ensure regional and technological alignment.
- Lock a dictionary — create a reusable “golden mapping” applied to future imports.
Canonical Dictionary (Starter)
stainless 18/8→Stainless steel, austenitic 18/8 (EU, 2024)cardboard→Paperboard, recycled content 80% (EU)truck med→Transport, freight, 16–32 t, EURO6 (EU)
Validation Checks To Enable
- Unit guardrails: reject unknown unit strings; enforce SI base units.
- Range checks: ensure plausible energy or material intensity (e.g., 0.1–20 kWh/unit).
- Region gates: restrict or flag datasets outside the target geography.
- Completeness: confirm all modules or stages are represented before assessment.
Handling Edge Cases
- No exact dataset match: select the nearest technology and document uncertainty.
- Mixed-year data: normalize to the study year or flag sensitivity.
- Supplier synonyms: maintain an alias list so future imports map automatically.
Audit & Traceability
- Save a mapping report — detailing old vs. new names, reasoning, and reviewer notes.
- Store unit conversion factors and their data sources.
- Maintain an exceptions log for verifier or auditor review.
✅ Sustainly’s centralized data system ensures every mapping, conversion, and revision stays transparent and reusable across your organization.
FAQ
Will AI ever map incorrectly?Occasionally — review regional and technological context before finalizing. Do I need to manage databases manually?
No. Sustainly’s AI harmonization works across standardized datasets, letting you focus on results rather than configuration. How do I keep mappings updated?
Version your dictionary and review quarterly — updates apply automatically across imports.
Why Use Sustainly
Sustainly combines transparent AI, automated data harmonization, and centralized sustainability data management — creating a single source of truth for all your product and supplier data.- Automated taxonomy and unit harmonization
- AI-assisted mapping with traceable approval flow
- Reusable mapping dictionaries across departments
- Centralized sustainability data system
- Scalable workflow for both experts and newcomers
Sustainly transforms messy spreadsheets into structured, auditable sustainability data — so your organization can move faster, stay consistent, and make confident, data-driven decisions.If you’re looking for a
software to measure product sustainability,
tool to calculate environmental impact of a product, or
sustainability analysis software for production processes, → Start with Sustainly and turn messy data into measurable sustainability insights.