Inventory & Operations
Safety Stock Calculator
Size a whole-unit stock buffer from summary statistics or paste actual daily demand and supplier lead times to derive them.
Your result
Safety stock
Enter average demand, its daily variation, lead time and its variation, then choose a service level.
Calculated on your device. Your numbers aren’t sent or saved.
The method
Size the buffer from uncertainty, not a flat guess
Daily demand can vary, and a delivery can arrive earlier or later than average. This model combines their variance during lead time, multiplies the resulting standard deviation by a service factor and rounds the buffer upward to whole units. It then adds average lead-time demand to show a related reorder point. The service level is a modeled probability of avoiding a stockout in one cycle—not the fill rate or a guarantee.
Example 1
A cent of a unit changes the whole-unit buffer
Suppose an item sells 40 units per day on average, with a daily standard deviation of 12 units. Supplier lead time averages 7 days with a 1-day standard deviation. Lead-time-demand variation is √(7 × 12² + 40² × 1²) ≈ 51.07 units. At a modeled 95% cycle service level, Z = 1.645, giving about 84.01 unrounded safety units. Round up to 85. Expected lead-time demand is 280 units, so the reorder point is 365.
- Demand variation over lead time
- ≈ 51.07 units
- Unrounded buffer
- ≈ 84.01 units
- Safety stock to hold
- 85 units
- Reorder point
- 365 units
Example 2
Stable supplier, variable demand
At 40 average units per day, 12 units of daily standard deviation, a fixed 7-day lead time and the same 95% factor, variation is 12 × √7 ≈ 31.75 units. The modeled buffer falls to about 52.22 units, rounded up to 53. The change isolates the effect of supplier lead-time variability; it does not promise fewer real stockouts.
- Lead-time SD
- 0 days
- Whole-unit safety stock
- 53 units
- Reorder point
- 333 units
Before you calculate
Assumptions & limits
- Use representative history for one item at one location. Daily demand standard deviation must be calculated from daily demand; lead-time standard deviation from actual supplier lead times. All demand is in the same units and all time is in days.
- The formula assumes demand and lead-time variation are approximately independent and that demand over replenishment lead time is sufficiently close to a normal distribution. Intermittent, strongly seasonal or promotional demand can make the estimate unreliable.
- The selectable 90%, 95%, 98% and 99% values are cycle service targets with approximate one-sided Z factors 1.282, 1.645, 2.054 and 2.326. Cycle service level differs from fill rate; neither is guaranteed by a static model.
- A zero standard deviation means that quantity is truly constant in the model, not that data is missing. If both are zero, the calculated safety buffer is zero. Do not replace missing history with zero without understanding the risk.
- Daily demand and its standard deviation accept 0–1,000,000 units with up to two decimals. Average lead time accepts 0.01–366 days; its standard deviation accepts 0–366 days. Statistical intermediate values display two decimals; operational stock recommendations round upward to whole units.
- Raw-history mode accepts 7–90 consecutive representative daily counts and 3–30 completed supplier lead times, separated by spaces, commas or new lines. It calculates sample standard deviations using n−1, rounds derived means and standard deviations to two decimals, then runs the same model. A small or biased sample can mislead.
Keep in mind
Common mix-ups
Using a fill-rate target as cycle service
A 95% fill rate and a 95% chance of no stockout per replenishment cycle are different objectives. This calculator models the latter.
Mixing weekly variation with daily demand
A weekly standard deviation cannot be entered as daily standard deviation without conversion. Keep observation intervals and lead-time units consistent.
Assuming normal demand for a slow-moving item
Intermittent demand can have many zero days and occasional spikes. The normal approximation may mislead; review an item-specific demand model instead.
Sources & calculation notes
Documents the combined demand and lead-time variability formula, service-factor examples, whole-unit rounding and normal-distribution limitation.
Explains why safety stock protects against demand and lead-time variation and how service factors affect stockout risk.
Calculation and input rules checked: . Engineering validation; no professional accounting review is claimed.