ETA Exception Alerter: Catch Late Shipments Before Your Customer Does

The problem this kills

A shipment was promised Thursday. It's now Tuesday, the last scan was four days ago in a yard three states away, and nobody noticed — until the customer calls, angry, asking where their freight is. By then you've lost the one thing that would have saved the relationship: time. Time to reroute, time to expedite, time to pick up the phone first and say "we're on it" instead of "let me check."

Late and at-risk shipments are almost always visible before they blow up. The promised ETA is in your TMS. The last scan date is in your tracking feed. The gap between "should have moved by now" and "hasn't moved" is sitting right there in the data. What's missing is something that checks every active load against those signals every morning, surfaces the handful that are slipping, and drafts the alert so a coordinator can review it and get ahead of the problem. You do not need to be a developer to build that something.

What you'll build

A simple internal web tool for your customer service and traffic teams. You import your active shipments — each with its promised ETA and its latest status / last-scan date. The tool computes days since the last scan and the ETA gap (how far past, or how close to, the promised date each load is), then flags every shipment as on-track, at-risk, or late using stale-scan thresholds you set — and it counts business days, so a quiet weekend or a holiday doesn't trip a false alarm. For each flagged load it drafts a plain-English internal alert and a customer-facing heads-up you can send. Your coordinator reviews the at-risk list and the drafted alerts, edits anything that needs it, and clicks Approve — and only then does the tool send the notice and write it to an escalation log.

What's inside the Implementation Plan

The downloadable plan is a step-by-step file you paste into an AI coding agent. It opens by interviewing you about your business — how shipments flow today and who watches them, the TMS or tracking system and spreadsheets you use, the exact columns and naming in your shipment data, your typical and peak load counts, the rules that make a shipment "at-risk" versus "late," and your real edge cases like weekend dwell, customs holds, and final-mile gaps. It reads a short spec back to you for a thumbs-up, then builds the tool around your answers instead of a generic template. From there it walks the agent through the data model, the CSV import, the exception engine (days-since-scan, ETA gap, business-day math), the at-risk review screen, the alert drafts, the human approval gate, and the escalation log and exports. Every step ends with a ready-to-copy prompt.

The governance it includes (this is the point)

This isn't a toy. The plan builds in the controls a real operation needs: login so only your team can use it, row-level security so people only see their own organization's shipments, a complete audit trail of every flag and every approve/skip decision (who, what, when, and why), a hard human-approval gate so no customer ever gets an alert until a coordinator signs off, and duplicate guards keyed on shipment ID so the same load can't be flagged and alerted twice in a day. The whole tool exists to make a careful human decision fast — the AI raises the flag and drafts the words, a person makes the call.

Who it's for

Customer service leads and traffic / dispatch managers who own on-time delivery and are tired of finding out a load is late from the customer. If you can describe what makes a shipment "at-risk" in your world — how stale a scan is too stale, and how close to the ETA is too close — you can build this.

You've got this — open the plan, paste the first prompt, and you'll be flagging your first at-risk loads this afternoon.