The max-minus-average method in full, computed from your inputs. Safety stock is the gap between the most you could sell over the longest wait and the demand you would expect under normal conditions — the cushion that bridges the two.
Scenario
Calculation
Units of demand
Worst case
15/day × 10 days
150
Normal case
10/day × 7 days
70
Safety stock ◀
Worst case − normal case
80
Estimates only — not financial, tax, or professional advice.
100% private — every number you enter is calculated in your browser and never sent to our servers.
What it calculates: Safety Stock, Max Demand During Lead, Average Demand During Lead.
Updated 5 June 2026 · Transparent assumptions
Peak demand across the worst lead time, less the normal case
This uses the classic formula: maximum daily demand times maximum lead time, minus average daily demand times average lead time. It sizes the buffer to cover a cycle where both things go wrong at once — unusually strong sales and an unusually slow supplier.
Its appeal is that every input is a number you can read off your own history rather than a statistical parameter. Its cost is conservatism: assuming both worst cases coincide holds more stock than a probabilistic method would.
The buffer is insurance, and insurance has a premium
Safety stock ties up capital, consumes storage and carries obsolescence risk, and it earns nothing while it waits. The inventory carrying cost calculator prices that at typically 15% to 30% of the stock value a year.
So the question is not how to eliminate stockouts but what service level is worth paying for. Going from 95% to 99% availability often costs considerably more buffer than the first 95% did, because you are covering rarer and more extreme cases.
A predictable high-volume product needs less buffer than an erratic small one
Two products selling the same quantity need very different buffers if one sells steadily and the other arrives in unpredictable bursts. The formula captures this through the gap between average and maximum, which is wide for erratic demand and narrow for steady demand.
The same holds for suppliers. A reliable supplier with a consistent 14 days needs far less protection than one averaging 10 days but ranging from 5 to 30.
No service level, no seasonality, no correlation
This method does not take a target service level, so it cannot tell you the probability of a stockout it protects against. Statistical methods using demand standard deviation and a service factor do, and are worth the extra inputs for high-value lines.
It also assumes the maxima you enter remain valid. Seasonal peaks, a viral product moment or a supplier changing factories all invalidate a buffer computed from last year’s extremes.
Sources & References
Figures on this page are checked against primary, authoritative sources. Links open in a new tab.
Results are estimates for planning and analysis based on the figures you enter. They are not accounting, tax, or financial advice — verify with your own records and a qualified professional before making decisions.
Published the calculator with its formula, worked example, assumptions, limitations and a bespoke guide, and added an automated formula test suite covering it.
Tested the max-minus-average buffer against hand-computed peak and normal demand across their respective lead times.
Tested that identical maximum and average figures produce no buffer at all, and that the result is never negative.
Add this calculator to your site
Responsive embed — and private: nothing your visitors type leaves their browser.