An AI prompt that turns cycle count results into a short variance note: what’s off, the likely reason, and the next step for each SKU.
Write a cycle count variance note for [location or zone] counted on [date]. Results: [paste SKU, description, system quantity, counted quantity and unit cost]. For each SKU with a variance over [threshold in units or dollars], show the difference in units and dollars, a likely reason based on [any context, such as recent receipts, picks or moves], and one next step such as recount, check receipts or adjust. Total the net variance at the top. Keep it under 250 words.
Net variance: −$412 across 4 SKUs.
Vic matches variances against receipts, picks and moves, suggests the next step, and holds the note for your approval.
The difference between the quantity your system shows and the quantity counted on the shelf for a SKU.
Common causes are mis-picks, receipts not yet put away, unrecorded damage, and moves between locations that were not recorded.
Recount large or unexplained variances first. Adjust once the cause is clear or the recount confirms it.
Any AI chat tool. Paste it, fill the fields, and review the draft before sending. In Vic, the facts fill in for you.
Today’s inbound and outbound appointments, grouped by door.
Open prompt → ChecklistA step-by-step check for a new supplier’s first delivery.
Open prompt → TextA short first message with lane, home time and pay type up front.
Open prompt →