How to predict stockouts before they happen

Stockouts are preventable

Running out of stock feels like it happens suddenly, but the warning signs are almost always visible in advance. Products don’t go from healthy inventory to zero overnight. They decline gradually, and that decline is trackable.

Learning to read stockout warning signs lets you reorder before you run out, preventing lost sales and frustrated customers.

The cost of stockouts

Stockouts hurt more than you might think.

Direct lost sales:

Customers who wanted to buy can’t. That revenue is gone. Some might return later, but many won’t.

Customer experience damage:

Customers who encounter stockouts lose confidence in your reliability. They might shop elsewhere next time, even when you have stock.

Marketing waste:

If you’re driving traffic to out-of-stock products, you’re paying for clicks that can’t convert. Ad spend is wasted.

Search and algorithm penalties:

Platforms may deprioritize products with poor availability. Stockouts can hurt your visibility even after you restock.

Days of supply: the core prediction metric

Days of supply tells you how long current inventory will last.

The calculation:

Current inventory units divided by average daily sales rate. If you have 100 units and sell 5 per day, you have 20 days of supply.

Why it predicts stockouts:

When days of supply drops below your lead time plus safety buffer, you’re at risk. If reordering takes 14 days and you want 7 days safety buffer, any product under 21 days of supply needs a reorder.

Automating the calculation:

Calculate days of supply for every product regularly. Flag products below your threshold automatically.

Setting appropriate thresholds

Different products need different stockout warning thresholds.

Lead time variation:

Products with longer supplier lead times need earlier warnings. A product with 30-day lead time needs alerts at 40+ days of supply. A product with 7-day lead time can wait until 14 days.

Demand variability:

Products with stable, predictable demand need less safety buffer. Products with volatile demand need more cushion because sales might spike unexpectedly.

Product importance:

Core products and bestsellers deserve more aggressive protection. Running out of your top seller is worse than running out of a slow mover.

Sales velocity tracking

Sales velocity changes over time. Static averages miss these shifts.

Recent velocity versus historical:

Compare last 7 days sales rate to last 30 days and last 90 days. If recent velocity is accelerating, your days of supply is shrinking faster than historical averages suggest.

Velocity trend detection:

Is the product speeding up or slowing down? Accelerating products approach stockout faster than expected. Decelerating products give you more time.

Seasonal velocity adjustment:

If you’re entering a high season, future velocity will exceed recent past. Adjust your projections for expected seasonal lift.

Reorder point calculation

The reorder point is the inventory level that triggers a new order.

Basic formula:

Reorder point = (Daily sales rate × Lead time) + Safety stock

Example:

Selling 10 units daily. Lead time is 14 days. Safety stock is 50 units. Reorder point = (10 × 14) + 50 = 190 units. When inventory hits 190, place a reorder.

Dynamic reorder points:

Recalculate reorder points regularly as sales velocity and lead times change. Static reorder points become outdated.

Lead time monitoring

Lead times aren’t always reliable. Track actual performance.

Supplier lead time tracking:

Record actual delivery time for each order. Compare to promised lead time. Some suppliers consistently deliver late.

Lead time variability:

High variability is dangerous. A supplier averaging 14 days but ranging from 10 to 25 days requires more safety stock than one consistently at 14 days.

Seasonal lead time changes:

Lead times often extend during peak seasons when suppliers are busy. Factor this into your planning.

Early warning dashboard

Build visibility into approaching stockouts.

Traffic light system:

Green: Adequate inventory. Yellow: Approaching reorder point. Red: Below reorder point, stockout risk.

Sorted by urgency:

Show products sorted by days of supply or stockout risk. Most urgent items at the top.

Daily review:

Check the dashboard daily. Stockout prevention requires consistent attention, not occasional review.

Demand spike detection

Sudden demand increases can cause unexpected stockouts.

Spike identification:

Monitor for sales significantly above normal. If a product suddenly sells 3x its usual rate, it will stockout 3x faster than projected.

Spike causes:

Marketing campaigns, viral social mentions, competitor stockouts, or press coverage can cause spikes. Try to anticipate known causes.

Spike response:

When you detect a spike, immediately recalculate days of supply and consider expedited reordering.

Supplier communication

Proactive supplier communication prevents some stockouts.

Forecasting to suppliers:

Share your demand forecasts with suppliers. They can prepare inventory and prioritize your orders.

Early warning requests:

Ask suppliers to alert you if they anticipate delays or their own stockouts. Early warning gives you time to find alternatives.

Expedited options:

Know what expedited shipping or production options exist. When stockout risk is high, the extra cost of expediting might be worth it.

Stockout pattern analysis

Learn from past stockouts to prevent future ones.

Stockout history review:

Which products have stocked out? When? Why? Look for patterns.

Common causes:

Demand forecasting errors? Supplier delays? Insufficient safety stock? Order timing mistakes? Identify your most common causes.

Process improvement:

Address the root causes of past stockouts. If supplier delays are common, increase safety stock or find backup suppliers.

Metrics for stockout prediction

Focus on these stockout prevention metrics:

Days of supply by product. Products below reorder point. Sales velocity trend (accelerating or decelerating). Actual versus expected lead times. Demand spike detection. Stockout frequency by product. Lost sales estimates from past stockouts. Supplier reliability scores.

Stockout prediction is about attention and process, not complexity. Calculate days of supply, set appropriate thresholds, monitor regularly, and act on warnings before inventory runs out.