Open-Order Aging Dashboard: See Every Stuck Order Before It Becomes a Problem

The problem this kills

Every morning someone on your team rebuilds the same picture by hand: which orders are open, what stage they're stuck in, and which ones have been sitting too long. They pull an export, sort it three ways, eyeball the dates, copy the scary ones into a "follow up today" tab, and ping whoever they think owns each one. By the time the picture is assembled, it's already stale — and tomorrow they do it all again.

The cost isn't the half hour. It's the orders that fall through the cracks because nobody had a consistent definition of "stuck." A credit-hold order that's been sitting eight days looks identical to one that landed yesterday when you're scanning a 600-row spreadsheet at 8am. The order that needed a call last Tuesday doesn't surface until the customer calls you, angry. And because the "board" lives in one person's spreadsheet, when they're out, the whole picture goes dark.

Open-order aging is a watch-list problem, not a memory problem. It deserves a real, shared, governed board that buckets every order by stage and age the same way every day — and tells you exactly which ones crossed the line.

What you'll build

A simple internal web app for your ops, fulfillment, and customer-service teams. You import your open orders (everything not yet shipped/closed, with its current stage and key dates). The board automatically buckets them by stage (e.g. new, credit hold, picking, packed, awaiting carrier) and by age within each stage, using aging thresholds you set per stage — so "3 days in picking" can be fine while "3 days on credit hold" is already a red flag.

You see the whole open-order picture at a glance: counts per stage, how many are healthy vs. aging vs. stuck, and the worst offenders highlighted. You drill into any bucket to see the orders inside it, assign an owner to the ones that need a human, and export the exceptions — the aged and stuck orders — as a clean follow-up list. The daily refresh is approved before the board updates (so a bad import never quietly replaces a good board), and every owner reassignment is confirmed before it's saved.

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 — what your real order stages are called, which date drives "age" at each stage, the exact column names and order-ID format in your export, your typical and peak open-order volumes, what counts as "too long" at each stage, who owns follow-up, and the messy exceptions (orders with no stage, orders that skip a step, re-opened orders, partial shipments). It reads a short tailored spec back to you and waits for your thumbs-up before it builds anything, so the board matches your order flow — not a generic template.

From there it walks the agent through the data model, the daily import with duplicate guards, the stage + age bucketing engine, the drill-in views, owner assignment, the exception export, and the approval gate on the refresh. Every step ends with a ready-to-copy prompt. There's a full "No API yet?" path that uses a Google Sheet / CSV as the data source and produces a clean exceptions export in the exact columns your follow-up process expects — so you can build and run the whole thing this afternoon regardless of what order system you're on.

The governance it includes (this is the point)

This board drives who chases which order, so the controls aren't optional. The plan builds in login so only your team can use it, row-level security so you only ever see your own organization's orders, a complete audit trail of who refreshed the board, who changed an owner, and who changed a threshold, a hard human-approval gate so a daily refresh isn't applied until someone reviews and approves it (and owner reassignments are confirmed before they save), and duplicate guards keyed on the order ID so the same order can't be loaded — or counted — twice across refreshes.

Who it's for

Ops managers, fulfillment leads, and customer-service team leads — anyone who currently rebuilds the open-order picture by hand each morning and is one sick day away from losing it entirely. If you can name your order stages and say how many days is "too long" at each one, you can build this.

You've got this — start with the plan, paste the first prompt, and answer the interview. You'll have your whole open-order picture on one screen before lunch.