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Safety stock calculator

The buffer inventory that protects against stockouts when demand or lead time varies: SS = Z·√(LT·σ_d² + d²·σ_LT²), where Z comes from your target service level. Enter demand, lead time and their variability, and it returns the safety stock and the reorder point.

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Enter Service level (%), Average daily demand, Lead time (days), Std dev of daily demand (σ_d), Std dev of lead time (σ_LT, days) and the Safety stock calculator works out Service factor Z, Safety stock (units), Reorder point (units) straight away. For instance, with Service level (%) = 95, Average daily demand = 40, Lead time (days) = 7, Std dev of daily demand (σ_d) = 12 and Std dev of lead time (σ_LT, days) = 2 it returns Service factor Z = 1.645, Safety stock (units) = 142 and Reorder point (units) = 422.

How to use it

  1. Enter your values: Service level (%), Average daily demand, Lead time (days), Std dev of daily demand (σ_d), Std dev of lead time (σ_LT, days).
  2. Read the result instantly: Service factor Z, Safety stock (units), Reorder point (units).

Frequently asked questions

How does the Safety stock calculator work?

It takes Service level (%), Average daily demand, Lead time (days), Std dev of daily demand (σ_d) and Std dev of lead time (σ_LT, days) and derives Service factor Z, Safety stock (units) and Reorder point (units) from them. The calculation is live as you type, so the result updates on every change.

Which values does the calculator ask for?

5 values: Service level (%), Average daily demand, Lead time (days), Std dev of daily demand (σ_d) and Std dev of lead time (σ_LT, days). Nothing else is required — no account, no file upload.

What does a typical calculation look like?

With Service level (%) = 95, Average daily demand = 40, Lead time (days) = 7, Std dev of daily demand (σ_d) = 12 and Std dev of lead time (σ_LT, days) = 2, the calculator returns Service factor Z = 1.645, Safety stock (units) = 142 and Reorder point (units) = 422. Those figures come from running this exact tool, so you can reproduce them by entering the same values.

How much does the result change with different inputs?

It moves a lot. Using Service level (%) = 190, Average daily demand = 80, Lead time (days) = 14, Std dev of daily demand (σ_d) = 24 and Std dev of lead time (σ_LT, days) = 4 instead, Service factor Z goes from 1.645 to 3.719 — which is why it is worth testing a few scenarios rather than trusting a single figure.

What does it give for smaller values?

Scaled down to Service level (%) = 47.5, Average daily demand = 20, Lead time (days) = 4, Std dev of daily demand (σ_d) = 6 and Std dev of lead time (σ_LT, days) = 1, Service factor Z comes out at 0. The relationship is worth checking at both ends before you rely on a single result.

When would I actually use this?

Running the week: issuing an invoice or a quote, knowing what is in stock and what to reorder, and seeing whether cash covers what is due.

What is the most common mistake?

Reading profit as cash. A profitable month with sixty-day payment terms can still leave the account empty — the two numbers answer different questions.

What is the difference between the Safety stock calculator and the Reorder point calculator?

Both return Reorder point (units). What differs is what they ask for: this one wants Service level (%) and Average daily demand, the Reorder point calculator wants Average daily demand (units) and Safety stock (units). Use whichever matches the numbers you already have.

Is there a tool for the next step?

Takt time calculator is the closest one after this: Compute the takt time — the pace of production needed to meet demand.

What else is worth having open alongside it?

Average collection period calculator and Inventory period calculator — they come up in the same task often enough to be worth a second tab.

Further reading

All guides →
ExplainerThe EOQ Square-Root Formula, and Where It Stops Being TrueEOQ = √(2DS/H) balances ordering cost against holding cost. Its most useful property is how flat the cost curve is around the optimum — and its four failure modes are quantity discounts, lumpy demand, a finite replenishment rate, and the two inputs nobody can measure.ExplainerProcess Capability: Cp, Cpk and What Six Sigma Actually ClaimsCp compares the spec width to the process spread; Cpk penalises being off-centre. A process can have an excellent Cp and still make scrap — here is the case, with defect rates computed from the normal distribution rather than read off a table.ExplainerGMROI: the Inventory Number That Outranks MarginGross margin return on inventory investment divides gross margin by the cash tied up in stock. It exists because margin alone ranks products wrongly: a 60% margin turning twice a year loses to a 25% margin turning twelve times.ExplainerThe Cash Conversion Cycle: the Number That Explains Why You Are Out of CashCCC = DIO + DSO − DPO. It is the number of days your cash is out of your hands, and it is the reason a profitable, growing business runs out of money. Worked end to end, with the negative-cycle case that makes suppliers your cheapest lender.ExplainerFixed-Charge Cover: the Ratio a Landlord or a Lender Looks AtThe same company, the same year, reads 1.02×, 1.52× or 2.56× depending on where rent is put and whether principal is grossed up for tax. Two of those pass a 1.25 covenant and one does not.ComparisonInterest Coverage and the Ratios a Lender Actually TestsA loan agreement's covenants are the ratios that can put a solvent, profitable company into default. Interest coverage, times interest earned and DSCR are not three measures — and the one that adds principal repayment is the one that bites.