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Inventory fundamentals

How to calculate a reorder point in Shopify (with safety stock)

Updated 21 August 2026 · 7 min read

A reorder point is the stock level at which you place a new order. Set it too high and you overstock; set it too low and you sell out while the next shipment is still in transit. Here is the exact formula, the safety-stock math that makes it reliable, and a full worked example.

The reorder point formula

At its core, a reorder point answers one question. How much stock covers me until the next delivery arrives?

Reorder point = (average daily demand × lead time in days) + safety stock Lead time is the number of days between placing an order and it being on your shelf, ready to sell.

The first part is demand during lead time, the stock you expect to sell while you wait. The second part is safety stock, the buffer that absorbs the weeks you sell faster than average and the shipment that turns up late. Leave the buffer out and you will stock out about half the time, because real demand lands above its average roughly half the time.

The safety stock formula

Safety stock depends on three things: how variable your demand is, how variable your lead time is, and how certain you want to be that you won't run out (your service level). The standard formula that accounts for both sources of variability is:

Safety stock = Z × √( LT × σd² + d² × σLT² ) Z = service-level factor · LT = average lead time (days) · σd = std. deviation of daily demand · d = average daily demand · σLT = std. deviation of lead time (days)

When your lead time is basically constant (σLT close to zero), this reduces to the simpler and very common version:

Safety stock = Z × σd × √LT

Choosing Z (your service level)

Z is simply how many standard deviations of buffer you want to hold. A higher service level means fewer stockouts but more cash tied up in inventory, so it is worth setting per product rather than one figure for the whole store:

Service levelZ factorGood for
90%1.28Low-margin or easily re-ordered items
95%1.65A sensible default for most products
98%2.05Important lines you don't want to miss
99%2.33Bestsellers and hero products

A full worked example

Say you sell a steady product, and from your Shopify order history you measure the following:

Average daily demand (d)12 units/day
Std. deviation of daily demand (σd)4 units/day
Average lead time (LT)10 days
Std. deviation of lead time (σLT)2 days
Target service level95% → Z = 1.65

Step 1, safety stock:

= 1.65 × √( 10 × 4² + 12² × 2² )
= 1.65 × √( 160 + 576 )
= 1.65 × √736
= 1.65 × 27.1 ≈ 45 units

Step 2, reorder point:

= (12 × 10) + 45
= 120 + 45 = 165 units

So once this product drops to 165 units in stock, it is time to place the next order. The 120 covers expected sales during the 10-day wait, and the 45-unit buffer covers the good weeks and the late shipments.

How much should you order?

The reorder point tells you when to order, not how much. For the quantity, many stores use a simple "order up to" target and cover the next few weeks of demand. The classic cost-optimal answer is the Economic Order Quantity:

EOQ = √( 2 × annual demand × order cost ÷ holding cost per unit ) It balances the cost of placing frequent small orders against the cost of holding large ones.

In practice, order cost and holding cost are fuzzy numbers, so most merchants settle on a target coverage, something like "reorder up to six weeks of demand", and adjust from there.

Doing this across a whole catalogue

The math above is per product. The hard part is not any single calculation. It is that every product has its own demand, its own variability and its own lead time, and all of them drift over time. A steady bestseller and a lumpy, once-in-a-while item need completely different treatment. The simple formula above assumes reasonably steady demand, whereas intermittent items call for methods like Croston's. Keeping all of that current by hand across a real catalogue is where spreadsheets tend to fall over.

The shortcut: your Shopify order history already contains every number these formulas need, including average demand, its variability and the sales patterns. A forecasting app can measure them per product and compute the reorder point for you, updated automatically.

Let Brimstock do this for every product

Brimstock reads your Shopify sales history and computes the reorder point, safety stock and suggested order quantity for each product, and shows you the reasoning. Free for up to 50 products.

Get Brimstock on the App Store

For the record, Brimstock is our app. The formulas above are standard inventory math and work the same no matter how you calculate them.

Frequently asked

What is a reorder point, in plain terms?

It is the stock level that triggers your next order. When a product's on-hand quantity falls to its reorder point, you order more, so the new stock arrives just as you are running low.

What Z value should I use?

For a 95% service level use Z = 1.65. Step up to 2.05 (98%) or 2.33 (99%) for products you really cannot afford to miss, and down to 1.28 (90%) for items that are cheap to hold or quick to reorder.

Does the reorder point tell me how much to order?

No, only when to order. For the quantity, use a target coverage (order up to a set number of weeks of demand) or the Economic Order Quantity described above.


Related: Shopify is retiring Stocky on 31 August 2026, and how to keep forecasting →