But collecting it can feel like herding cats — suppliers, factories, and internal teams each hold small but crucial pieces of the puzzle. This guide helps you structure your first data-collection process with clarity, confidence, and minimal chaos.
Why Primary Data Matters
- 🌱 More accurate than generic databases
- 🔍 Helps identify real hotspots in your production or supply chain
- 🏆 Strengthens internal decision-making and customer trust
- 📈 Supports data-driven sustainability improvements
Who to Ask (and What to Ask For)
| Source | What to Request |
|---|---|
| Internal factory | Material inputs/outputs, energy, water, waste |
| Supplier | Transport modes, packaging, recycled content |
| Logistics | Shipping distances, load factors |
| Assembly partners | Assembly energy, scrap rates, equipment types |
🛠️ Sample Data Table (for Suppliers)
| Parameter | Value | Unit | Notes |
|---|---|---|---|
| Material input | 1,250 | kg | Polymer resin |
| Electricity | 1,900 | kWh | Annual total |
| Transport | 700 | km | Plant → warehouse |
| Scrap rate | 8 | % | Injection molding |
5 Golden Rules of Primary Data Collection
- Start simple — focus on major materials, energy use, and transport first.
- Avoid perfectionism — approximate values are better than no values.
- Document source & year — avoid losing context in anonymous spreadsheets.
- Ask for ranges — low/average/high values help reflect uncertainty.
- Keep a clean audit trail — consistent naming and version control save hours.
A clean data structure today means faster, scalable sustainability workflows tomorrow.
Tools That Make It Easier
- Google Forms or Typeform for supplier inputs
- Shared folders (Notion, SharePoint) for internal logs
- Excel sheets with dropdown fields for units
- Flags missing or inconsistent units
- Helps standardize materials across suppliers
- Organizes primary data in a centralized sustainability hub
- Supports both experts and beginners as they scale their assessments
Common Pitfalls to Avoid
❌ Sending massive, complex spreadsheets nobody understands❌ Requesting data suppliers don’t track
❌ Mixing years without documenting the difference
❌ Forgetting to standardize units
❌ Assuming one email will get a reply — follow-up is essential
Final Tip
Your first LCA is always the hardest. The second becomes dramatically easier when your data is structured, centralized, and easy to update — especially with transparent AI sustainability tools supporting your workflow.Start Structured
Build a simple, repeatable data format from day one.
Scale Confidently
Use AI-assisted workflows in Sustainly to expand across products and teams.