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AI agent for logistics engineers

Automation Business Case Validation Agent

A business case whose assumptions are tested against history before decision makers see it

Automation Business Case Validation Agent: what goes in, what the agent does and what you get

What it does

Automation cases often rest on optimistic volumes and labor savings. This agent rebuilds the case from volume forecasts, labor data and vendor quotes. It runs low and high scenarios and checks every assumption against history, such as actual peak volumes, absence rates and past project overruns. Weak assumptions are revised and the case is rerun. It lists the risks and the break-even point in plain terms. The engineer approves the summary for decision makers. The summary shows payback in every scenario and names the assumption that matters most. Edge case: the vendor quote excludes integration work, so the agent adds an estimate and marks it as such.

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 An automation proposal is submitted 2 USES A TOOL Load forecasts, labor data and the vendor quote 3 DOES Rebuild the cost and savings model 4 USES A TOOL Compare each assumption with history 5 CHECKS THE RESULT Is every assumption inside the historical range? If not: replace it with the historical value and markthe change. Back to step 3. 6 DOES Run low, expected and high scenarios 7 CHECKS THE RESULT Does the case pay back in the target period in thelow scenario? If not: revise scope or volume assumptions and rerun.Back to step 3. 8 DOES Write the summary with break-even and risks 9 YOU APPROVE Engineer approves the summary for decision makers 10 RESULT Business case filed
Read the steps as a list
  1. An automation proposal is submitted
  2. Load forecasts, labor data and the vendor quote
  3. Rebuild the cost and savings model
  4. Compare each assumption with history
  5. Is every assumption inside the historical range?If not: replace it with the historical value and mark the change. Back to step 3.
  6. Run low, expected and high scenarios
  7. Does the case pay back in the target period in the low scenario?If not: revise scope or volume assumptions and rerun. Back to step 3.
  8. Write the summary with break-even and risks
  9. Engineer approves the summary for decision makersThe agent waits here for your OK.
  10. Business case filed

How it decides

An assumption stands when it is within the historical range. Outside it, the agent uses the historical value and shows the gap.

  • Use the lowest of forecast and last year's volume for the low case
  • Add 15 percent for integration if the quote omits it
  • Reject labor savings that assume 100 percent utilization
  • Show payback in the low and high cases

Make it yours

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

  • Target payback period
  • Contingency percentage (default 15)
  • Scenarios
  • Cost items included

What keeps you in control

It always asks you first

  • The summary for decision makers

Hard limits

  • Never present a case with untested assumptions
  • Never contact vendors

It stops when

  • Done: case tested and approved
  • Stop: no historical data to test against

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 sorter quote assumed 1.2 million parcels and 6 operators saved. History showed a peak of 0.9 million and 4 operators on the line. The check failed, so the agent used history and payback moved from 2.1 to 3.4 years. It added $90,000 for integration. The engineer approved the revised summary.

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