Article · · 6 min read
How to build a daily warehouse ops brief with AI in 10 minutes (with a fake dataset you can download)
Every morning you turn two exports into a picture of the day by hand. It takes twenty minutes when nothing is broken. It is the first thing that gets skipped when something is.
Here is the ten-minute version. Two exports, one saved prompt, one page. The kit calls it the Morning Read. Everything below runs on a fake warehouse you can download, with an answer key, so you can check the page before you trust it on your own building.
The loop, six steps
Pull two exports. Shipments, one row per shipment: order ID, order timestamp, ship timestamp, carrier, service, cost, status. Labor hours, one row per person per day: date, employee ID, function, regular hours, overtime hours. Last two weeks of each. Same folder, same file-name pattern, every day. That folder is the morning drop.
Delete the name column. Before the file leaves your laptop. Employee IDs and hours go in. Names, pay rates, and addresses do not. If the export cannot be produced without names, it does not get uploaded.
Paste the prompt. The one below. Attach the two files, or paste the two tables if your tool will not take attachments. (Paste-only window? Pivot first.)
Read the page. Three lines, one table, up to five questions, the gaps, the formulas.
Verify one number by hand. A different one each day. Thirty seconds in Excel.
Post it. One page, printed, on the board by the time clock. At the huddle, point at one row and ask one question. Four minutes.
The prompt
This is the short form, written for a plain chat window. It works in ChatGPT, Copilot, or whichever tool your company approved.
The Morning Read · short formUsing only the two tables I paste below (shipments; labor hours), build a one-page morning brief for the latest ship date in the data — never today's date. Compare each metric to the same weekday one week earlier. Metrics: orders shipped; median hours from order to ship (clock hours); % of orders shipped within 24 hours; ship cost per order; hours worked; OT % overall and by department (top 3). Show formulas in footnotes. If a metric cannot be computed from these tables, leave it blank and list it under "Gaps" with the reason — never estimate. Do not mention or rank any individual; use IDs only. End with up to five questions for the floor, each tagged [FLOOR CHECK].
If your tool can run code, add one line: "Compute using code and show every formula in a footnote."
The full version in the kit has six blocks: who the tool is, what each file is, every term defined against a column name, the rules, the exact page you want, and three flags ([FLOOR CHECK], [UNVERIFIED], [GAP]). The definitions block does most of the work. Report day = the latest ship timestamp. Same weekday = report day minus seven. OT % = overtime ÷ (regular + overtime). When a number comes back wrong, the fix is almost always a definition, not a request to be more careful.
What comes back on the practice warehouse
Files: shipments.csv and labor.csv, one month of Copperline Fulfillment Co., a fictional 3PL generated by script. Report day is Tuesday 2026-03-31, the latest ship timestamp in the file. Same weekday is Tuesday 2026-03-24. This is the tested output, as it came back.
Needs attention today
- PACK and PICK carried all of the day's overtime on fewer orders than last Tuesday (907 vs. 976): building OT 12.8%, PACK 27.5%, PICK 25.6%.
- Ship cost per order rose while the expedite share fell (1.5% of shipments vs. 3.4%): $19.10 vs. $18.62, +$0.48.
- Click-to-ship did not move: median 25.4 clock hours, with 46.3% of orders out within 24 clock hours (last Tuesday 25.2 h and 45.8%).
| Metric | Report day (Tue 03-31) | Same weekday (Tue 03-24) | Delta | Flag |
|---|---|---|---|---|
| Orders shipped | 907 | 976 | −69 | |
| Median click-to-ship (clock hrs) | 25.4 | 25.2 | +0.2 | |
| Shipped within 24 clock hrs | 46.3% | 45.8% | +0.5 pt | |
| Ship cost per order | $19.10 | $18.62 | +$0.48 | [FLOOR CHECK] |
| Hours worked | 385.3 | 408.5 | −23.3 | |
| OT % (building) | 12.8% | 17.7% | −4.9 pt | [FLOOR CHECK] |
| OT % by function (top 3) | PACK 27.5% · PICK 25.6% · all other functions 0.0% | PUTAWAY_REPLEN 39.3% · PACK 35.0% · RECEIVE 24.5% | — | [FLOOR CHECK] |
What it didn't do
It didn't call the day good or bad. It didn't name a packer. It didn't tell you what to do. It told you where to look, with the number that says so.
The questions it wrote for the floor do the rest. Was a pack station down, or did the work land late? Short crew in PICK, or waiting on replenishment? Those are yours to answer, not the tool's.
The blanks, and why each one is right
The same page listed six gaps. All six are correct.
| Left blank | Why |
|---|---|
| Units per labor hour | No units column in either file. It can't be computed, so it isn't. |
| Pick units per hour | No order-lines file. Same reason. |
| Anything about inventory | No adjustments or on-hand file was given. |
| Labor cost per order | The labor file carries wage bands, not rates. A band is not a rate. |
| Plan variance | No plan total was pasted. |
| Targets or bands | None were pasted, so no metric is judged against a threshold. |
Six blanks is a good sign. A tool that fills them is a tool that made six numbers up. Gaps stay blank, flagged.
Verify one number by hand
Today's number is building OT %. Open labor.csv. Filter to 2026-03-31. Sum the overtime column: 49.25 hours. Sum regular plus overtime: 385.25 hours. Divide: 12.8%. It matches.
Tomorrow pick a different row. If a number ever doesn't match, nothing else on the page is trusted until you know why. This step catches the brief that runs three weeks on an OT % with regular hours as the denominator.
Common failures, and the line that fixes each
| What you see | Why it happened | The line to add |
|---|---|---|
| Report day is today, or the date in the filename | You never defined it | "Report day = the latest ship timestamp in the file." |
| Compared to yesterday | The tool's default | "Same weekday, not yesterday." Say it twice. |
| A units-per-hour figure | It filled a gap | "Units per labor hour is NOT computable from these files. Leave it blank." |
| A packer named or ranked | The people rule wasn't in the prompt | "Use IDs only. Never rank, name, or single out an individual." |
| "Strong day for the team" | Tone drift | "Plain language. No adjectives about performance." |
| Totals off by a little | Arithmetic done in prose | "Compute using code. Show every formula in a footnote." |
Two or three passes and the prompt is stable. Save it where your tool keeps standing instructions. After that the morning is: attach, type one line, read.
Never
- Never let the tool pick the report day. The data picks it.
- Never paste names, wages, or confidential files. Delete the column first.
- Never accept a filled gap. If the file can't support a number, the page shows a blank and a reason.
- Never post a page you can't explain at the huddle. If the honest answer to "how'd you get that?" is "the AI said so," you don't have a number. You have a rumor.
- Never let it write to anything. It reads exports. That's all.
The close
Ten minutes: pull, strip, paste, read, check one number, post. The page above is what working looks like. If yours matches on the fake building, run it on your own export tomorrow. If it doesn't, fix the definition, not the tone.
The prompt above is #1 of the twelve free prompts. Before it runs on a real export, read the ten rules once.
Your company's AI and data policy wins. Never paste names, wages, or confidential files.
— Floor Read
Sources: morning-read/shipments.csv, morning-read/labor.csv — Copperline practice warehouse, fictional.
Written by a sitting director of operations at a large distribution center — eight years on fulfillment floors, from frontline supervisor to running a multi-hundred-person building's P&L. No software vendor pays for a mention here. The author keeps the day job and the brand separate, which is why there's no headshot; the sample chapter is free so you can judge the work instead.