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AI agent for sustainability analysts

Life Cycle Inventory Data Gap Agent

Close or document every material data gap and show how it affects the result.

AnalysisScience and research
See how it worksGet access
Life Cycle Inventory Data Gap Agent: what goes in, what the agent does and what you get

What it does

A life cycle assessment study often finds, late, that some inputs have no data or that datasets use different boundaries, so the results are not comparable. This agent lists every input and output in the product system and checks each against the goal and scope: the functional unit, system boundary and cut-off rule. It flags items with no data, data from a different region or year, and data that covers a different boundary. For each gap it searches for a proxy dataset and scores how well it fits. It then tests how much each gap or proxy changes the result by varying it, and reruns the model. It focuses effort on the gaps that matter. It never adopts a proxy by itself. The analyst approves. Edge case: a gap below the cut-off rule is documented, not filled.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Inventory built or changed 2 USES A TOOL Load the inventory and the goal and scope 3 DOES Check each input and output for data, region, yearand boundary 4 DOES List gaps and mismatches 5 USES A TOOL Search databases for proxy datasets and score fit 6 USES A TOOL Run the model with each proxy and with high and lowvalues 7 CHECKS THE RESULT Does any gap change the result by more than thecut-off? If not: document the gap as immaterial and keep theproxy note. Back to step 5. 8 CHECKS THE RESULT Is the proxy fit good enough for each material gap? If not: search for a better dataset or request primarydata. Back to step 4. 9 DOES Write the data gap report with sensitivity results 10 YOU APPROVE Analyst approves proxies and documented gaps 11 RESULT Gap register and updated inventory
Read the steps as a list
  1. Inventory built or changed
  2. Load the inventory and the goal and scope
  3. Check each input and output for data, region, year and boundary
  4. List gaps and mismatches
  5. Search databases for proxy datasets and score fit
  6. Run the model with each proxy and with high and low values
  7. Does any gap change the result by more than the cut-off?If not: document the gap as immaterial and keep the proxy note. Back to step 5.
  8. Is the proxy fit good enough for each material gap?If not: search for a better dataset or request primary data. Back to step 4.
  9. Write the data gap report with sensitivity results
  10. Analyst approves proxies and documented gapsThe agent waits here for your OK.
  11. Gap register and updated inventory

How it decides

It ranks gaps by their effect on the result in a sensitivity test, and treats a gap as material when varying it changes the result by more than the cut-off.

  • Treat a gap as material when it changes the result by over 1%
  • Prefer data of the same region and year
  • Do not fill gaps below the cut-off, only document them
  • Ask for primary data when no proxy scores well

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Materiality threshold (default 1%)
  • Variation range for tests
  • Databases to search
  • Cut-off rule
  • Report format

What keeps you in control

It always asks you first

  • Use of each proxy
  • Documented immaterial gaps

Hard limits

  • Never replace data without a recorded reason
  • Document every proxy with its source

It stops when

  • Done: all material gaps closed or approved
  • Stop: no suitable proxy and no primary data

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA packaging LCA had 31 flows. Seven had gaps. The agent found proxies for six and tested each by plus and minus 30%. Only the adhesive moved the result, by 3.2%, and its best proxy was a different region. It asked for supplier data. After that came in, the effect fell to 0.8%. The analyst approved the remaining proxies.

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