Inventory Reorder Point & EOQ Calculator

What is a reorder point, and how is it different from safety stock?

A reorder point is the inventory level that triggers a new purchase order — when your stock count hits this number, you order more. Safety stock is one of the two components that make up the reorder point; the other is lead time demand.

The formula is: Reorder Point = Lead Time Demand + Safety Stock. Lead time demand is how much you'll sell or use while waiting for a new order to arrive (average daily demand × lead time in days). Safety stock is the extra buffer that protects you when demand spikes or the shipment runs late.

Most free calculators stop at "safety stock = a number you pick." That's a guess, not a calculation. A better approach ties safety stock to a target service level (say, 95% of order cycles won't stock out) and the actual variability in your demand and lead time — which is what separates a reorder point you can defend to a boss or auditor from one you made up on a Tuesday.

How do I calculate economic order quantity (EOQ)?

EOQ = √(2 × Annual Demand × Ordering Cost ÷ Holding Cost per Unit). It's the order size that minimizes the combined cost of placing orders (which favors ordering rarely, in bulk) and holding inventory (which favors ordering often, in small batches).

Say you sell 12,000 units a year, it costs $75 to place an order, and holding cost runs 25% of a $25 unit cost ($6.25/unit/year). EOQ = √(2 × 12,000 × 75 ÷ 6.25) = √288,000 ≈ 537 units. Order in batches of 537, roughly every 16 days, and you're at the mathematical sweet spot — order bigger and holding costs eat the savings; order smaller and you're paying ordering costs too often.

What's a good safety stock level — how much buffer is normal?

There's no universal number; it depends on how badly a stockout would hurt you and how unpredictable your demand and lead times are. As a rough guide: 90% service level works for low-consequence items (a stockout is an inconvenience), 95% is the common default for most commercial inventory, and 99% is reserved for items where running out is genuinely costly — a production line component, a top-selling SKU, a life-safety part.

Bumping the service level from 90% to 99% doesn't scale linearly — going from 95% to 99% roughly adds 40% more safety stock (Z-score jumps from 1.65 to 2.33) for a relatively small gain in stockout protection. That's why blindly choosing "99% just to be safe" quietly inflates your carrying costs. Pick the service level the item's cost of failure actually justifies.

Should I switch to my calculated EOQ if I'm already ordering "enough" and never stocking out?

Not stocking out isn't the same as ordering efficiently — it just means your current quantity, whatever it is, happens to be large enough. The question EOQ answers is whether you're paying more than you need to for that safety margin.

Using the calculator's defaults: ordering 1,000 units at a time costs $5,088 a year in combined ordering and holding costs. Switching to the EOQ of 537 units drops that to $4,417 — a savings of $671 a year, on one SKU, with the same safety stock and the same protection against stockouts. Run this across a few dozen SKUs and the number stops being trivial. If your calculated savings come back small, your current quantity is probably already close to optimal — the calculator will tell you either way rather than assuming.

What's the difference between reorder point and reorder quantity, and why do I need both?

Reorder point tells you when to order; reorder quantity (EOQ) tells you how much. They answer different questions and you need both to run inventory properly — knowing you should reorder at 630 units doesn't help if you don't know whether to order 100 or 1,000 units when you do.

Think of it as a two-part rule: "When inventory drops to 630 units, place an order for 537 units." The reorder point protects you from stockouts during the lead time window; the EOQ keeps the cost of that ordering cycle as low as possible. Calculators that only give you one or the other leave you solving half the problem by guesswork.