This tool tells you when to replenish each SKU: multiply average daily demand by supplier lead time, then add safety stock. The result is a stock trigger, measured in units, that tells you when to place an order.
However, that trigger only works when demand, delivery times, and inventory records reflect reality. Start with one product, calculate its threshold, and then apply the same structure across your catalog.
Key Takeaways
- Calculate reorder point as average daily demand multiplied by lead time, plus safety stock.
- Compare the trigger with inventory position, including outstanding orders and customer commitments, to avoid duplicate purchases.
- Give seasonal products separate triggers, and review buffers when demand or supplier reliability changes.
Use the Ecommerce Reorder Point Calculator Formula
The standard reorder point formula combines expected demand during replenishment with an extra buffer:
Reorder point = (average daily demand × supplier lead time) + safety stock
This formula sets a unit threshold for replenishment. The first part is lead time demand. If a SKU sells 50 units daily and replenishment takes 10 days, lead-time demand is 500 units. Add 300 units of safety stock, and the reorder point becomes 800 units.
These published examples show how different inputs change the trigger.
| Example | Daily demand | Lead time | Safety stock | Reorder point |
|---|---|---|---|---|
| Qoblex product example | 50 units | 10 days | 300 units | 800 units |
| ShipFusion snow globes | 20 units | 10 days | 100 units | 300 units |
| Fishbowl headphones | 7 units | 5 days | 35 units | 70 units |
These are calculation examples, not recommended stock levels for your products.
In Qoblex’s example, 1,200 units on hand leaves 400 units above the trigger. At 50 units daily, that means approximately eight days until reorder: (1,200 − 800) ÷ 50.
Eight days until the reorder trigger doesn’t mean eight days until stockout. The trigger leaves inventory to cover the replenishment period.
Measure Demand and Lead Time Consistently
Calculate unit demand using available selling days
Average daily usage (unit sales per day) = units sold ÷ days measured
Use units, not order counts, to calculate daily sales, since one order can contain several units. Qoblex recommends a 90-day starting window and excluding out-of-stock days.
That exclusion matters because unavailable products can’t record their full demand. However, it doesn’t reconstruct lost sales or remove seasonal bias. Compare periods with similar pricing, promotion exposure, and availability.
For shared inventory, combine demand across channels without duplicating orders. Keep sizes and colors separate when they have different SKUs. Don’t let strong sales for one variant inflate another variant’s replenishment trigger.
Measure the complete replenishment delay
Average lead time = total delivery days across orders ÷ number of orders
Measure the time between placing an order and having sellable stock available. Include production, transit, receiving, and inspection where applicable. Also use matching time units: daily demand requires lead time in days.
Fishbowl recommends using the longest lead time when deliveries are inconsistent. Treat that as a conservative planning choice, then review whether your safety stock already covers the same delays.
Before changing thresholds, reconcile physical and recorded inventory. A larger buffer won’t repair missing receipts, damaged stock counted as sellable, or channel synchronization failures.
Build a Spreadsheet-Ready Reorder Point Calculator
Google Sheets or Excel can calculate each SKU’s trigger without custom software. Use one row per SKU and fulfillment location when stock isn’t freely interchangeable.
Enter the Qoblex example in row 2 using this layout. Column H applies the reorder point formula to calculate the threshold.
| Column | Field | Entry or formula |
|---|---|---|
| A | SKU | Your product identifier |
| B | Average daily demand | 50 |
| C | Lead time in days | 10 |
| D | Safety stock | 300 |
| E | Sellable on-hand units | 1200 |
| F | Outstanding inbound units | 0 |
| G | Unfulfilled committed units | 0 |
| H | Reorder point | =ROUNDUP(B2*C2+D2,0) |
| I | Inventory position | =E2+F2-G2 |
| J | Order alert | =IF(I2<=H2,"REORDER","HOLD") |
The ROP is 800 units, the inventory position is 1,200 units, and the alert is HOLD.
Copy the formulas down the sheet, but enter SKU-specific inputs. Round thresholds up to whole units; supplier case packs affect the eventual order quantity separately.
This structure assumes column E hasn’t already deducted the commitments in column G. Otherwise, you’d subtract the same customer demand twice. Keep damaged goods and uninspected returns outside sellable on-hand stock.
Size Safety Stock Around Demand and Delivery Variability
Calculate the max-minus-average buffer
ShipFusion and Fishbowl use a method also described in SPS Commerce’s safety stock guidance:
Safety stock = (maximum daily sales × maximum lead time) − (average daily sales × average lead time)
A safety stock calculator can apply this calculation to SKU inputs. For ShipFusion’s snow globes, average demand is 20 units daily, peak demand is 30, and lead time is 10 days:
Safety stock = (30 × 10) − (20 × 10) = 100 units
The reorder point is therefore (20 × 10) + 100 = 300 units.
Although some guides call this a max-min method, the subtraction uses average demand and average lead time, not minimum values.
Recognize when the formula overstates protection
The method assumes maximum demand and maximum lead time could coincide. A bulk order combined with lead time variability or supply chain disruptions can create an expensive buffer and lead to overstocking.
It also doesn’t translate directly into a target service level. Moving toward a higher target, such as 95%, generally requires more protection, but this formula doesn’t prove you’ve reached that target.
For repeatable, high-volume demand, statistical safety-stock methods can use demand variability and a chosen service target. For intermittent or promotion-driven demand, examine lead-time demand patterns rather than relying on one daily maximum.
Avoid stacking overlapping allowances. Using the longest delivery time in base demand while also adding a delay-based buffer can produce more protection than intended.
Calculate Separate Triggers for Seasonal Demand
A trailing average can misrepresent seasonal fluctuation, underestimating peak demand and overestimating demand after the season ends. Use demand forecasting to set the trigger from expected demand during the upcoming replenishment period.
Using ShipFusion’s snow globe figures, these calculations isolate the effect of changing daily demand while holding the 100-unit buffer constant.
| Planning period | Daily demand | Lead time | Buffer | Trigger |
|---|---|---|---|---|
| Quieter period | 20 units | 10 days | 100 units | 300 units |
| Peak-demand period | 30 units | 10 days | 100 units | 400 units |
The peak trigger rises by 100 units because daily sales increase from 20 to 30 units over the same 10-day period. Review the peak-season buffer separately if demand variability or delivery delays increase.
Compare sell-through by SKU and season alongside stock cover and availability to review inventory levels. Activate seasonal triggers early enough for inventory to arrive before demand increases.
Near the selling season’s end, stop automatic replenishment when another delivery would arrive too late to sell.
Apply Stock Triggers Across Your Catalog
Compare the threshold with inventory position
For the spreadsheet model, compare inventory levels by calculating inventory position:
Inventory position = sellable on-hand units + outstanding inbound units − unfulfilled customer commitments
Trigger an order when inventory position reaches or falls below the ROP. This prevents repeated alerts from creating duplicate purchase orders while replenishment is already underway.
Inventory position alone doesn’t show whether incoming goods will arrive in time. Review inbound dates against projected demand. A late purchase order can leave you exposed even when inventory position looks sufficient.
Split records by location when transfers aren’t fast enough to support customer promises. Also include component demand when bundles and individual products consume the same stock.
Give each SKU an owner and review rhythm
Choose the safety stock buffer according to demand uncertainty and the cost of a shortage. Dependable hero products may deserve more protection than short-lived products with high leftover risk.
Review active replenishment SKUs weekly, with daily exception monitoring during fast-moving campaigns to catch stockouts before they affect orders. As the process grows beyond a spreadsheet, inventory management software can apply the same SKU-level inputs and logic.
Recalculate after supplier changes, persistent delays, major promotions, or a sustained demand shift. Record the inputs, effective date, owner, and reason for each change. Track stockouts, then measure SKU-level stockout rates to see whether availability improves.
If inbound stock can’t support a campaign, reduce exposure or promote suitable in-stock alternatives. Increasing a spreadsheet threshold won’t accelerate a late shipment.
Frequently Asked Questions
How does reorder point differ from EOQ?
Reorder point answers when to order. Economic order quantity, or EOQ, estimates how much to order by balancing ordering and holding costs.
Your actual purchase quantity may also depend on minimum orders, case packs, cash availability, and remaining seasonal demand. An 800-unit reorder point doesn’t mean you should order 800 units.
Are inventory days the same as a reorder point?
No. Inventory days, also called days in inventory, is a financial measure:
Inventory days = (ending inventory value ÷ COGS) × days in the period
For an annual calculation, the period commonly contains 365 days. Use matching cost-based values, not units divided by dollars.
Reorder point is a SKU-level unit threshold. Inventory days helps assess inventory investment, but it doesn’t replace a replenishment alert.
Keep Every Stock Trigger Tied to Operating Conditions
A useful reorder point combines expected replenishment demand with a deliberate buffer. Its reliability depends on accurate inventory, realistic delivery times, and demand estimates that match the next selling period.
Start with your priority SKUs and review exceptions before automating purchases. Keep trigger calculations and inbound timing together so the next order arrives while customers still need the product.
