Safety stock calculator
Work out how much buffer stock to keep so a busy week or a late delivery does not leave you sold out. Three methods, from the quick rule of thumb to the statistical formula. Free, no signup.
Uses your worst recent day and your slowest delivery. No statistics needed.
How much daily sales swing around the average. In a spreadsheet: =STDEV(range of daily sales).
How many days deliveries usually come early or late.
Keep this much on hand on top of what you expect to sell during the lead time.
- Demand during lead time
- 140
- Reorder point
- 212
- Safety stock in days of sales
- 7.2
- Cash tied up in safety stock
- –
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ReorderSheet calculates safety stock, reorder points and order quantities for all your SKUs at once from the order and inventory CSV exports you already have. You get a list of what to reorder, how many units and when each SKU runs out. $29 once, runs in your browser, files are never uploaded.
Safety stock formulas
1. Max minus average. The quickest method. It plans for your worst normal day and your slowest normal delivery happening at the same time.
It is easy to explain and needs no statistics, but it tends to overstock fast movers because it assumes both worst cases at once.
2. Service level with demand variability. Sizes the buffer by how much daily sales swing and how often you accept a stock-out.
3. Service level with demand and lead time variability. Use this when your supplier is not reliable.
Z values for common service levels
- 90% service level: Z = 1.28
- 95%: Z = 1.65
- 97.5%: Z = 1.96
- 98%: Z = 2.05
- 99%: Z = 2.33
Going from 95% to 99% raises safety stock by about 40%. Use high service levels for best sellers and products where a stock-out loses the customer, and lower ones for slow movers.
Worked example
A product sells 10 units a day on average, 16 on a busy day. Delivery takes 14 days, at worst 20.
- Max − average: 16 × 20 − 10 × 14 = 320 − 140 = 180 units
- Service level 95%, daily sales swing by 4 units: 1.65 × 4 × √14 ≈ 25 units
- Same, plus deliveries vary by 3 days: 1.65 × √(14 × 16 + 100 × 9) ≈ 56 units
The gap between 25 and 180 units is why the method matters. The rule of thumb is safe but ties up cash; the statistical methods keep less stock for the same protection, as long as your inputs are realistic.
Where the numbers come from in Shopify
- Daily sales and their swings: export orders for the last 90 days, count units per SKU per day and calculate average and standard deviation. Leave out days when the item was sold out.
- Lead time: from the day you send the purchase order to the day the goods are sellable, from your own records per supplier.
Common mistakes
- Counting sold-out days as zero-sales days. That makes demand look lower and more erratic than it is.
- Using one service level for the whole range. Slow sellers with 99% service level tie up cash for months.
- Never updating the inputs. Recalculate when sales or suppliers change, at least every quarter.