1INBOUND
Every carton gets a slot
The principal's PO lands in X-IN. Each carton is scanned into a rack location, and anything not put away stays visible as overflow.
Case study · Warehouse and retail operations · Aug to Oct 2026
Five files.Now one WMS.
A plush toy brand sold through 8 stores of 3 retailers, and its stock lived in five files that never talked to each other. I connected warehouse, shipments, field visits and sell-out into one system on Google Sheets and Apps Script, as the operations lead, with AI writing the code.
Ferdy Febrian IskandarOperations and dataJakarta
2:00 walkthrough. Animated scenes use sample data; real-screen clips come from the live board with retailer names and values blurred.
On shelf · 01
16% → 28%of stock on store shelves, first measured 22 Aug, 27.7% on 8 OctStores · 02
8stores across 3 retailers, served from 1 warehouseSKU · 03
43active SKUs on one movement ledgerLicence · 04
Rp0licence cost per monthThe problem
Five files, five answers
XLSXSKU master.xlsx
Total stock
2,277
XLSXPO principal.xlsx
Incoming
+360
SHEETSStock HO
Total stock
2,239
SHEETSDaily sales
Total stock
1,979
XLSPartner sales.xls
Sold
?
The stock count on 14 August gave three different totals for the same warehouse. Every number was typed again by hand, deliveries to stores had no proof, field visits could not be checked, and partner reports arrived as PDF or Excel in a different shape each time. So the ask was simple: connect it all.
What I built
One flow, shelf to sell-out
2WAREHOUSE CONDITION
Every shelf, accounted for
A live map of racks, tables and stacks with fill levels. Quantity per rack has to match HO stock, and every count correction is logged with who, when and why.
3OUTBOUND
Pick, pack, prove it
Pickers scan the slot first, then the SKU. A delivery order cannot be issued when the store requires a PO number and none is entered.
4SHIPMENTS
Closed only on receipt
Every shipment moves through five stages and only closes when the store confirms it arrived, so a stalled parcel shows up the same day.
5FIELD OP APP
From the shelf, straight to the board
Store staff use a phone app that writes to the same ledger.
- Check-in only inside 300 m of the store, with a selfie
- Shelf counts become ledger rows, variances flagged
- Shelf photos trigger a Google Chat alert
- Check-out computes hours on site
6SELL-OUT
Every sale, one ledger
Partner sales reports in PDF or Excel are read into ledger rows, so sell-out per store and SKU is visible, including the SKUs that never sold.
How I built it
Built by ops, powered by AI
I own the rules
The data model and the business rules that must never break are mine. A few of them:
No PO number, no delivery order.
A count correction is logged, never overwritten.
No check-in outside 300 m of the store.
AI writes the code
I describe the behaviour and the rule, AI writes the Apps Script, and every change gets a test that is first shown to fail before the fix goes in. I deploy and run production functions myself.
Built on what the team already uses
No new licence and no IT team. One movement ledger is the source for every number on the board.
Google SheetsApps ScriptGoogle ChatExcel scan station