Sandhya Indurkar

Math, Applied

Will We Run Out? Probability of Stockout in Real Inventory Decisions

Inventory level crossing a reorder line with stockout risk callout

The idea

Inventory teams rarely ask whether stockout is possible. They ask if the risk is acceptable. Probability turns that into a clear decision: if we reorder at this level, what are the chances demand outruns supply before the next shipment arrives?

Reorder too late and customers see “out of stock”. Reorder too early and cash gets trapped on shelves. The right point is a business choice, but probability makes the tradeoff explicit.

Better question than “will we stock out?”: “what stockout risk are we willing to run?”

Example: reorder point vs stockout probability

Set a reorder point and see the probability of running out during supplier lead time. This helps inventory decisions move from gut feel to explicit risk.

Cafe chain restock: weekend spikes make stockouts expensive.

Lead-time demand

840 bags

Reorder point

900

Stockout probability

20.9%

Stockout risk curve (%)

Lower reorder points look efficient, but risk stockouts. Higher points reduce risk but tie up more inventory.

Stockout risk is 20.9%. This can work for low-margin items, but watch lost sales and service complaints.

The math

Demand during lead time

lead-time demand ≈ normal(μL, σ√L)

Mean demand scales with lead time. Variability scales with the square root of lead time. That gives a distribution of possible demand before restock arrives.

Risk definition

stockout probability = P(demand during lead time > reorder point)

Pick a reorder point and compute the area of the demand curve beyond it. That area is your stockout risk.

Operational readout

service level = 1 - stockout probability

Many teams set service-level targets by SKU tier, then back into reorder points that meet those probabilities.

A simple application: restock policy before a promotion

A skincare SKU usually sells 85 units per day, but promo weeks are volatile. Lead time is 10 days. At a reorder point of 900, stockout risk is high enough to hurt conversion and ad efficiency. Raising reorder to 1,200 drops risk materially and protects campaign spend.

Reorder point: balance stockout risk and inventory drag

Move demand, lead time, and reorder point. See how fast stockout risk drops as you add buffer.

Reorder 980 gives ~78% service level (22% stockout risk)

Stockout risk by reorder point (%)

Demand vs reorder buffer

Lead-time demand: 855 · Reorder point: 980 · Safety stock: 125

Stockout risk

22%

Safety stock

125 units

Carrying index

115

Optimize (move here)

  • Set reorder points by target service level per SKU tier
  • Review supplier lead-time variability monthly

Hold (do not over-react)

  • One reorder rule for every SKU regardless of volatility

Escalate if

  • Stockout risk > 20% on revenue-driving items

Risk is high for customer-facing SKUs. Raise reorder point or shorten lead time.

The habit: show reorder points with explicit stockout probability in planning docs. This keeps inventory decisions aligned with customer experience and working capital.