When to use it
Use it before a weekly purchase review when you need to scan many SKUs and decide which ones need supplier orders now.
Use this CSV inventory reorder point calculator when your SKU list lives in a spreadsheet. Upload rows with current stock, average daily sales, lead time, and optional incoming stock to calculate reorder point, days left, risk label, and suggested reorder quantity.
Use it before a weekly purchase review when you need to scan many SKUs and decide which ones need supplier orders now.
Reorder point = average daily demand x lead time days + safety stock. Inventory position is current_stock + incoming_stock.
The calculator assumes your demand rate and lead time are reasonable for the next replenishment cycle. It shows fallback notes when demand is estimated from recent sales totals.
| Field | Why it matters |
|---|---|
| current_stock | Units available to sell right now. |
| average_daily_sales | Typical units sold per day. If blank, use recent sales totals in CSV mode. |
| lead_time_days | How many days replenishment usually takes. |
| incoming_stock | Units already ordered and expected to arrive. |
| minimum_order_quantity | Supplier MOQ used to round the suggested reorder quantity. |
If a SKU sells 4.5 units/day, supplier lead time is 21 days, and safety stock is 31 units, reorder point = 4.5 x 21 + 31 = 126 units. If inventory position is 32 units, the SKU is Reorder now.
Do not rely on the result alone when a promotion, supplier holiday, marketplace ranking change, or cash limit is likely to change demand or replenishment.
It is the inventory position where you should place a replenishment order before stock runs out.
Yes. Inventory position is current stock plus incoming stock, so open purchase orders reduce the suggested reorder quantity.
Yes. Use the CSV calculator to process multiple products and export the result table.
Found a confusing result, CSV issue, formula edge case, or wording problem? Send a short note. Please do not include sensitive SKU names, stock levels, costs, prices, sales numbers, or full CSV files.