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AI agent for sustainability analysts

Supplier Emissions Data Quality Escalation Agent

A supplier emissions dataset where every entry is verified, corrected or clearly marked as estimated

Quality controlScience and research
See how it worksGet access
Supplier Emissions Data Quality Escalation Agent: what goes in, what the agent does and what you get

What it does

Supplier emissions data arrives late, in different units, or as an estimate with no notice. This agent checks each submission for completeness, unit errors and implausible year-on-year changes, such as a halved total with no explanation. It requests corrections, and if a supplier does not respond, substitutes a spend-based estimate and records the change. It flags the effect on the total so the analyst can see how much of the number is estimated. After replies it rechecks. The analyst approves the dataset. Edge case: a supplier reports 0.4 tons for a plant that normally reports 400, so the agent flags a likely unit error.

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, continueApprovedYes, continueApprovedNoNo 1 STARTS WHEN Reporting cycle opens or submission arrives 2 USES A TOOL Read the submission and prior-year data 3 DOES Check completeness and units 4 CHECKS THE RESULT Is the submission complete, in the right units andwithin the plausible range? If not: list the issue and draft a correction request.Back to step 3. 5 YOU APPROVE Analyst approves the correction requests 6 USES A TOOL Send the requests and read replies 7 CHECKS THE RESULT Did the supplier reply with a corrected submissionby the deadline? If not: apply a spend-based estimate and mark the entryas estimated. Back to step 6. 8 DOES Calculate the effect of estimated entries on thetotal 9 DOES Draft the quality summary 10 YOU APPROVE Analyst approves the dataset 11 RESULT Verified supplier dataset
Read the steps as a list
  1. Reporting cycle opens or submission arrives
  2. Read the submission and prior-year data
  3. Check completeness and units
  4. Is the submission complete, in the right units and within the plausible range?If not: list the issue and draft a correction request. Back to step 3.
  5. Analyst approves the correction requestsThe agent waits here for your OK.
  6. Send the requests and read replies
  7. Did the supplier reply with a corrected submission by the deadline?If not: apply a spend-based estimate and mark the entry as estimated. Back to step 6.
  8. Calculate the effect of estimated entries on the total
  9. Draft the quality summary
  10. Analyst approves the datasetThe agent waits here for your OK.
  11. Verified supplier dataset

How it decides

A submission passes when it is complete, uses the right units and changes by less than the allowed range from last year without explanation.

  • Flag a change above 40% from last year without explanation
  • Flag values off by a factor of 10 or 1000 as likely unit errors
  • Use spend-based estimates only after the second request
  • Mark every estimate in the dataset

Make it yours

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

  • Change threshold (default 40%)
  • Reminder schedule
  • Estimation factors
  • Units accepted

What keeps you in control

It always asks you first

  • Correction requests sent to suppliers
  • Final dataset

Hard limits

  • Never changes a supplier's reported value without a reply
  • Never hides estimated entries

It stops when

  • Done: every entry verified or estimated and approved
  • Stop: submission format is unreadable

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 happensSupplier 33 reported 0.4 tons of CO2 for a plant that reported 410 last year, so the range check failed. The agent flagged a likely unit error and drafted a request. The supplier replied with 412 tons. Supplier 52 never replied after two requests, so the agent applied a spend-based estimate of 95 tons and showed it moved the total by 0.8 percent. The analyst approved.

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