Formula used
Safety stock = z-score x square root of lead time demand variance plus lead time variance. The z-score comes from the selected service level.
Search intent: Users want to estimate buffer inventory.
Safety Stock Calculator for Spreadsheet Inventory
This safety stock calculator estimates the buffer stock needed to cover demand changes and supplier delays. It uses service level, demand variability, lead time, and lead time variability. If sales history is thin, it uses a visible fallback instead of hiding the assumption.
Single-SKU calculator
How the calculation works
Fallback behavior
When there are not enough 30-day sales periods, demand variability is estimated as 20% of average daily demand and shown in the explanation.
Choosing service level
Use lower service levels for slow or low-margin items and higher levels for products where stockouts are costly.
Input fields explained
| Field | Why it matters |
|---|---|
| average_daily_sales | Base demand level for the SKU. |
| last_30_days_sales / last_60_days_sales / last_90_days_sales | Used to estimate demand variability when available. |
| lead_time_days | The replenishment window safety stock must cover. |
| lead_time_variability_days | Extra uncertainty from supplier delays. |
| desired_service_level | Controls how conservative the buffer should be. |
Worked example
If average demand is 4.5 units/day, demand variability fallback is 0.9 units/day, lead time is 21 days, lead time variability is 4 days, and service level is 95%, the calculator uses z-score 1.65 and returns safety stock of 31 units.
Common mistakes
- Treating safety stock as the same thing as reorder point.
- Leaving lead time variability at zero when suppliers often arrive late.
- Using a 99% service level for low-margin slow movers.
When not to rely on the result
Do not rely on the result when recent sales history is not representative, such as a launch week, clearance sale, seasonal spike, or stockout period.
FAQ
What service level should I use?
95% is the default. Use 90% for less critical items and 98-99% for high-demand products where stockouts hurt.
What if I lack daily sales data?
You can provide average_daily_sales or recent 30/60/90 day sales totals.
Is this a forecast?
No. It is a formula-based estimate from your uploaded or typed inputs.