How to work out your reorder point

The formula, the z table, a worked example, and the three cases where this formula quietly gives you a wrong answer. There is a calculator below, but the point of this page is that you can do it on paper afterwards.

The formula

Three inputs, and each one is worth being careful about:

• Demand per day — units sold ÷ days in the period. Use a period long enough to cover at least one lead time, and count the days the shop was actually open.
• Lead time — the days between placing the order and the stock being sellable on your shelf. Not the number your supplier quotes: add their handling, customs, and your own receiving. Most people underestimate this, and it is the input the answer is most sensitive to.
• Service level — the share of lead times you are willing to get through without running out. z comes from it:

The reorder point is when to order, not how much. When stock on hand plus stock already on order falls to this number, you place the order.

Work out yours

This runs in your browser. Nothing is sent anywhere — the page is blocked from making network requests at all, which you can check by turning your internet off and reloading.

This calculator is the textbook formula. If any of the three cases below apply to your catalogue, the number you just worked out by hand is wrong.

Why safety stock uses a square root

This is the part most sources get wrong, and getting it wrong is expensive in a way nobody notices — it does not cause a stockout, it just quietly parks your cash in a warehouse.

Demand over a lead time is a count of events: so many orders arrive, each for a unit or two. Counts like that follow a Poisson distribution, and the defining property of a Poisson distribution is that its variance equals its mean. The standard deviation is therefore the square root of expected demand — not a percentage of it, and not proportional to it.

So doubling your lead time does not double the buffer you need — it multiplies it by about 1.41 (that is √2). Demand over the window doubles, but the uncertainty around it grows only by the square root. Here is the same SKU at four lead times, buffered both ways:

The linear column anchors on the same 30-day buffer of 20 units and scales it with lead time, which is what "double the lead time, double the buffer" gives you. At a 120-day lead time it holds twice the buffer that is actually called for. On one SKU that is 40 units of dead cash; the reason it matters is that you apply this rule to every SKU you stock, and a container-shipped catalogue is mostly long lead times.

The same arithmetic runs the other way at short lead times: scaling down linearly leaves you under-buffered on fast-turning items, which is where stockouts actually happen.

A worked example

One SKU, every step visible, so you can repeat it in a spreadsheet.

How much to order is a different question

The reorder point tells you when. The quantity depends on how often you review stock — if you check weekly, each order has to cover the lead time and the week until you look again:

For SS-CREAM-50 on a weekly review with 12 units on hand and nothing on order: 5 × 37 = 185, plus 20 safety, minus 12 = 193 units. Then round to your supplier's case size.

Three ways this formula misleads you

The arithmetic above is correct and still gives a badly wrong answer in three common cases. All three are measured failures, not hypotheticals — the numbers come from building the tools on this site.

If you want to see where availability already cost you before you change anything, the free stockout cost calculator takes the same orders export and prices the gaps — with all three of the corrections above applied. See it run on sample data if you do not have an export handy.

If you would rather not do this per SKU every week

Everything above is on this page for free, and doing it by hand for your top twenty SKUs is a perfectly reasonable afternoon. It is the every week, for every SKU, with the three corrections applied part that stops happening. That is what the paid tool is for.

A real run of the free stockout calculator, not a mockup: an orders export goes in, the columns are detected, the number comes out. The paid tool takes the same file and points it forwards.

You give it your order history and your stock levels; it produces the decision, not a dashboard:

Every weekday gets its own rate, whole-shop zero days are discarded first, safety stock uses the square root, and any SKU with no sales in the recent half of your history is refused an order quantity rather than given a small one. Each SKU it declines to size is listed with the reason — nothing is silently dropped.

No server. That is the whole architecture.

One HTML file. Your order history and stock levels are read by JavaScript already in your browser and go nowhere — the file ships a Content-Security-Policy of default-src 'none', so the browser blocks every outbound request. Turn off your internet and it works identically. There is nothing to cancel and no vendor who can raise your price later.

Honest comparison

If you reorder weekly from one location and a re-export is no burden, the monthly fee buys you convenience you may not need. If you run multiple warehouses or need live sync, buy the app instead — this is not trying to be that, and saying so is cheaper for both of us than a refund.

Not for you if

• You have fewer than about 20 SKUs — a spreadsheet, or the calculator at the top of this page, is genuinely fine
• You need multi-location allocation or supplier MOQ optimisation
• Your catalogue is almost entirely seasonal — most of it would be excluded
• You want a dashboard to look at rather than an answer to act on

Requirements

Order history CSV with a date, a SKU and a quantity — Shopify, Amazon, WooCommerce, or your own spreadsheet. Stock on hand CSV is optional, but needed for order quantities rather than just reorder points. Any modern browser. No installation.