Free tool

Safety stock & reorder point calculator

Work out how much buffer stock you need to hit a target service level, and the inventory level that should trigger a new order. All calculations run in your browser — nothing is sent anywhere.

Mean demand per period (e.g. units per week). Use the same period unit everywhere.
CV = standard deviation ÷ average demand.
Per-period standard deviation of demand, in units.
Time from placing an order to receiving it, in the same period unit.
Leave empty if your lead time is reliable. If supplied, the full variable-lead-time formula is used.
Probability of not stocking out during one replenishment cycle.

Results

Fill in the inputs above to see your safety stock and reorder point.

Before you trust this number

This classic formula assumes demand is roughly normally distributed around a stable average. That holds for fast, steady movers — but for intermittent or lumpy demand (many zero-demand periods with occasional spikes, which is typical for spare parts and slow movers) it can badly mislead, in either direction. See our guide to safety stock & reorder points, or check your item first with the demand pattern classifier.

NextDemand exists because of exactly this gap — it classifies every item and applies a forecasting method that fits its pattern.

Frequently asked questions

What is safety stock?

Safety stock is buffer inventory held on top of expected demand to absorb variability — demand coming in higher than forecast, or a supplier delivering later than planned. Without it, any above-average cycle ends in a stockout. The formula sizes the buffer from the variability of demand over the lead time and your target service level.

What service level should I choose?

95% is a common default. Use higher levels (97.5–99%) for items where a stockout is expensive or safety-critical, and lower ones for cheap, easily substituted items. Note the cost is non-linear: moving from 95% to 99% raises the safety factor z from 1.645 to 2.326 — roughly 40% more safety stock for that item.

Does this formula work for intermittent or lumpy demand?

No. The formula assumes demand each period is roughly normal, and intermittent series — mostly zeros with occasional demands — violate that badly. The standard deviation becomes unstable and the resulting buffer is often far too high or far too low. For such items, use methods designed for intermittent demand (Croston, SBA, or empirical quantiles) instead of a z-score formula.