Inventory

Inventory Forecasting: Never Run Out of Stock

Published January 2025 • 12 min read

Stockouts cost businesses sales, customer loyalty, and reputation. Overstocking ties up cash and leads to markdowns or waste. The solution is accurate inventory forecasting - predicting what you'll need before you need it.

This guide covers practical forecasting methods that work for small businesses, from basic calculations you can do in a spreadsheet to more sophisticated approaches as you grow.

Average revenue lost to stockouts in retail businesses

The True Cost of Getting Inventory Wrong

Stockout Costs

Lost sales: Customers buy elsewhere
Lost customers: 21-43% won't return after a stockout
Rush shipping: Emergency orders cost more
Reputation damage: Reliability perception drops
Staff time: Managing disappointed customers

Overstock Costs

Tied-up capital: Money that could be earning returns
Storage costs: Warehouse space isn't free
Obsolescence: Products expire or become outdated
Markdowns: Selling at discount to clear stock
Insurance: Higher premiums for more stock

The Hidden Cost: Every dollar of excess inventory costs about 25-30 cents per year to hold (storage, insurance, depreciation, opportunity cost). $100,000 in excess stock costs you $25,000-$30,000 annually.

Basic Demand Forecasting Methods

1. Simple Moving Average

The simplest forecasting method: average your recent sales to predict future sales.

Simple Moving Average Formula

Forecast = (Sales Period 1 + Sales Period 2 + ... + Sales Period n) / n

Example: 3-month moving average
January: 100 units, February: 120 units, March: 110 units
April forecast = (100 + 120 + 110) / 3 = 110 units

Best for: Products with stable, consistent demand

Limitations: Doesn't account for trends or seasonality

2. Weighted Moving Average

Give more weight to recent periods, which often better reflect current conditions.

Weighted Moving Average Formula

Forecast = (W1 × Period 1) + (W2 × Period 2) + (W3 × Period 3)

Example: Weights: 50% (most recent), 30%, 20%
March: 110 × 0.5 = 55
February: 120 × 0.3 = 36
January: 100 × 0.2 = 20
April forecast = 55 + 36 + 20 = 111 units

3. Seasonal Forecasting

For products with predictable seasonal patterns, use last year's data adjusted for growth.

Seasonal Forecast Formula

Forecast = Last Year Same Period × (This Year YTD / Last Year YTD)

Example:
December last year: 500 units
Jan-Nov this year: 3,300 units
Jan-Nov last year: 3,000 units
Growth factor = 3,300 / 3,000 = 1.1
December forecast = 500 × 1.1 = 550 units

Calculating Reorder Points

The reorder point tells you when to place an order so stock arrives before you run out.

Basic Reorder Point Formula

Reorder Point = (Daily Sales Rate × Lead Time) + Safety Stock

Example:
Daily sales: 10 units
Supplier lead time: 14 days
Safety stock: 50 units
Reorder Point = (10 × 14) + 50 = 190 units

When your stock level hits 190 units, it's time to reorder.

Safety Stock Calculations

Safety stock is your buffer against uncertainty - unexpected demand spikes or supplier delays.

Simple Method

Simple Safety Stock

Safety Stock = (Maximum Daily Sales × Maximum Lead Time) - (Average Daily Sales × Average Lead Time)

Example:
Max daily sales: 15 units
Max lead time: 18 days
Avg daily sales: 10 units
Avg lead time: 14 days
Safety Stock = (15 × 18) - (10 × 14) = 270 - 140 = 130 units

Service Level Method

For more precision, calculate safety stock based on your desired service level (the percentage of demand you want to fulfil from stock).

Service Level	Z-Score	Risk of Stockout
90%	1.28	10%
95%	1.65	5%
97.5%	1.96	2.5%
99%	2.33	1%

Service Level Tip: A 95% service level is common for most products. Reserve 99% for your best-sellers or products where stockouts are particularly costly.

Economic Order Quantity (EOQ)

EOQ tells you the optimal order size that minimises total inventory costs (ordering costs + holding costs).

EOQ Formula

EOQ = √((2 × Annual Demand × Order Cost) / Holding Cost per Unit)

Example:
Annual demand: 1,200 units
Cost per order: $50 (admin, shipping, receiving)
Holding cost per unit: $2/year
EOQ = √((2 × 1,200 × 50) / 2) = √60,000 = 245 units

Order 245 units at a time for optimal costs. With 1,200 annual demand, that's about 5 orders per year.

ABC Analysis: Focus Where It Matters

Not all inventory items deserve equal attention. ABC analysis categorises items by value and volume:

Category	% of Items	% of Value	Management Approach
A Items	~20%	~80%	Tight control, frequent reviews, accurate forecasting
B Items	~30%	~15%	Moderate control, regular reviews
C Items	~50%	~5%	Simple controls, infrequent reviews, higher safety stock

ABC in Practice: Your A items (top 20% of SKUs by value) deserve sophisticated forecasting. For C items, simple reorder points with generous safety stock often work fine.

Accounting for Seasonality

Many products have predictable seasonal patterns. Here's how to incorporate them:

Step 1: Calculate Seasonal Indices

Compare each month's sales to the annual average:

Month	Sales	Index (Sales / Monthly Avg)
January	80	0.80
February	85	0.85
...	...	...
December	150	1.50
Annual Avg	100	1.00

Step 2: Apply Indices to Forecasts

Seasonal Adjustment

Seasonal Forecast = Base Forecast × Seasonal Index

Example:
Base forecast (growth-adjusted): 110 units/month
December index: 1.50
December forecast = 110 × 1.50 = 165 units

Lead Time Management

Lead time variability is often the biggest source of forecasting error. Reduce it where possible:

Strategies to Reduce Lead Time

Multiple suppliers: Backup options when primary supplier is slow
Local sourcing: Shorter shipping distances
Vendor-managed inventory: Supplier monitors and replenishes
Standing orders: Pre-scheduled regular deliveries
Buffer stock at supplier: They hold stock ready to ship

Track Lead Time Variability

Order	Expected Lead Time	Actual Lead Time	Variance
1	14 days	16 days	+2
2	14 days	13 days	-1
3	14 days	18 days	+4

Use average and maximum actual lead times in your reorder point calculations.

Demand Signals to Watch

Forecasting isn't just about historical data. Watch for signals that demand is about to change:

Leading Indicators

Quote requests: Increase in customer enquiries
Competitor activity: Their stockouts = your opportunity
Market trends: Industry reports and news
Economic indicators: Consumer confidence, employment
Weather forecasts: For weather-sensitive products

Internal Signals

Website traffic: More visitors = more future orders
Cart abandonment: Price sensitivity or availability concerns
Customer feedback: Requests for products you don't stock
Sales team input: Pipeline and customer conversations

Common Forecasting Mistakes

Ignoring lost sales: If you were out of stock, you don't know true demand. Estimate what you would have sold.
Using only averages: Averages hide variability. A product that sells 0 units for three months then 400 units has an average of 100 - but that's not useful for forecasting.
Not adjusting for promotions: A spike from a sale shouldn't inflate your regular forecast.
Forgetting about new products: They have no history. Use analogous products or market research.
Set-and-forget: Forecasts need regular review and adjustment.
Ignoring supplier reliability: A cheap supplier with unreliable delivery is expensive.

Building Your Forecasting Process

Weekly Inventory Review:

Check stock levels against reorder points
Review items approaching reorder point
Note any unusual demand patterns
Update forecasts for any changed circumstances
Place orders as needed

Monthly Forecast Review:

Compare actual sales to forecasts
Calculate forecast accuracy (actual vs predicted)
Update forecasts for next 3-6 months
Adjust safety stock levels if needed
Review supplier lead times
Update ABC classifications quarterly

When to Increase Safety Stock

New product launches (demand uncertainty)
Supplier quality issues
Holiday/peak seasons approaching
Lead time has become variable
Product is critical (stockout very costly)
Upcoming promotions or marketing campaigns

When to Decrease Safety Stock

Product demand has stabilised
Supplier reliability has improved
Lead time has shortened
Cash flow is tight (but be careful)
Product is end-of-life
Storage space is constrained

Track Your Inventory Smarter

Use BizziKit's free inventory manager to track stock levels, set reorder points, and never run out of your best-sellers.

Open Inventory Manager

Key Takeaways

Start simple: Moving averages work for stable demand products
Calculate reorder points: Know when to order before you run out
Include safety stock: Buffer against demand and supply variability
Use ABC analysis: Focus effort on high-value items
Account for seasonality: Adjust forecasts for predictable patterns
Track lead times: Supplier reliability affects your stock levels
Review regularly: Forecasts need constant refinement
Watch for signals: Leading indicators predict demand changes

Final Tip: The goal isn't perfect forecasting - it's reducing uncertainty to an acceptable level. Start with the basics, measure your accuracy, and improve over time.