Inventory management isn't a single discipline — it's a collection of techniques, each solving a different problem. The businesses that manage inventory well aren't necessarily using the most advanced software or the biggest warehouse teams. They're using the right combination of techniques for their specific situation.
This article covers ten proven inventory management techniques. Some are strategic (how you think about inventory), some are operational (how you handle it day-to-day), and some are mathematical (how you calculate the right quantities). Most businesses will benefit from combining several of these rather than relying on any single approach.
If you're new to the fundamentals, our guide to inventory management covers the basics before diving into specific techniques. For a complementary look at how businesses physically monitor and record stock movements, see our guide to inventory tracking methods.
1. Just-In-Time (JIT)
What It Is
Just-In-Time inventory means receiving goods only when they're needed for production or sale — not before. The goal is to minimise the amount of inventory sitting in your warehouse at any given time.
JIT was pioneered by Toyota in the 1970s and became one of the defining principles of lean manufacturing. The core idea is simple: inventory that's sitting on a shelf isn't adding value. It's tying up cash, consuming warehouse space, and risking obsolescence or damage.
How It Works in Practice
A food manufacturer using JIT might schedule raw material deliveries to arrive the morning they're needed for production, rather than stockpiling a week's worth of ingredients in cold storage. A retailer might replenish shelves daily from a distribution centre rather than holding weeks of stock in the back room.
Example: A bakery that uses 200kg of flour per day arranges daily deliveries of exactly 200kg, rather than receiving 1,000kg on Monday and storing it all week. The result: less cold storage needed, less risk of spoilage, and less capital tied up in flour.
When It Works
JIT works best when:
- Suppliers are reliable — if your flour delivery doesn't show up, you can't bake
- Demand is predictable — you need to know what you'll need and when
- Lead times are short — the gap between ordering and receiving is hours or days, not weeks
- You have strong supplier relationships — JIT requires coordination and trust
When It Doesn't
JIT is risky when supply chains are fragile. The COVID-19 pandemic demonstrated this clearly — businesses running pure JIT had no buffer when suppliers couldn't deliver. Similarly, businesses importing goods with long lead times (common in New Zealand, given our geographic isolation) often can't achieve true JIT.
The practical approach for most NZ businesses is "JIT-inspired" rather than pure JIT: keep inventory as lean as reasonably possible while maintaining a safety buffer for supply chain uncertainty.
2. ABC Analysis
What It Is
ABC Analysis categorises your inventory into three groups based on value and importance:
- A items: High value, typically 10-20% of SKUs but 70-80% of total inventory value
- B items: Moderate value, typically 20-30% of SKUs and 15-25% of value
- C items: Low value, typically 50-60% of SKUs but only 5-10% of value
The principle comes from the Pareto observation (the "80/20 rule"): a small percentage of your products account for the majority of your inventory value and business impact.
How It Works in Practice
Once you've classified your inventory, you apply different management strategies to each category:
A items get the most attention. You monitor stock levels closely, review reorder points frequently, negotiate the best supplier terms, and keep accurate demand forecasts. These are the products where a stockout costs you the most — or where overstock ties up the most capital.
B items get moderate attention. Standard reorder points, periodic review, reasonable safety stock. They matter, but they don't need daily monitoring.
C items get simplified management. Higher safety stock ratios (because running out of a $2 widget shouldn't stop a $50,000 production run), less frequent reviews, and possibly automatic reordering.
Example: A manufacturing business has 2,000 SKUs. Analysis reveals that 150 SKUs (their speciality raw materials) account for 75% of inventory spend. These become A items with weekly demand reviews and tight reorder management. The remaining 1,850 SKUs — packaging, fasteners, cleaning supplies — are managed with simpler rules.
Why It Matters
Without ABC analysis, businesses tend to apply the same level of management effort to everything. This means either over-managing low-value items (wasting time) or under-managing high-value items (wasting money). ABC analysis directs your attention where it has the most impact.
3. Economic Order Quantity (EOQ)
What It Is
EOQ is a formula that calculates the optimal order quantity — the amount you should order each time to minimise the combined cost of ordering and holding inventory. It balances two competing costs:
- Ordering costs: Every purchase order has a cost — staff time to create and process it, shipping fees, receiving and inspection effort
- Holding costs: Every unit in storage has a cost — warehouse space, insurance, capital tied up, risk of spoilage or obsolescence
Order too frequently in small quantities and your ordering costs are high. Order infrequently in large quantities and your holding costs are high. EOQ finds the sweet spot.
The Formula
EOQ = √(2DS / H)
Where:
- D = Annual demand (units per year)
- S = Cost per order (fixed cost each time you place an order)
- H = Annual holding cost per unit
Example: You sell 10,000 units per year of a product. Each order costs $50 to process and receive. Holding cost is $2 per unit per year.
EOQ = √(2 × 10,000 × 50 / 2) = √500,000 = 707 units
So you should order approximately 707 units at a time, which means about 14 orders per year.
Practical Considerations
EOQ is a useful starting point, but it assumes constant demand, constant lead times, and no quantity discounts — none of which are true in the real world. Use it as a guideline, then adjust for reality:
- If your supplier offers a 10% discount at 1,000 units, it might be worth ordering above EOQ
- If demand is seasonal, you'll need to adjust EOQ for peak and off-peak periods
- If you're space-constrained, EOQ might suggest quantities that simply don't fit
Most inventory management software can calculate EOQ automatically based on your historical data, which is far more practical than running the formula manually for hundreds of SKUs.
4. Safety Stock
What It Is
Safety stock is the buffer inventory you hold above your expected needs to protect against uncertainty — unexpected demand spikes, supplier delays, quality issues, or any other disruption that could cause a stockout.
It's the inventory equivalent of an emergency fund. You hope you don't need it, but when you do, it prevents a small problem from becoming a big one.
How to Calculate It
The basic formula is:
Safety Stock = (Maximum Daily Usage × Maximum Lead Time) − (Average Daily Usage × Average Lead Time)
Example: You typically sell 50 units per day with a 5-day lead time from your supplier. But sometimes demand spikes to 70 units per day, and occasionally the supplier takes 7 days.
Safety Stock = (70 × 7) − (50 × 5) = 490 − 250 = 240 units
So you'd hold 240 units of safety stock to cover the worst realistic combination of high demand and slow supply.
Getting the Balance Right
Too much safety stock and you're wasting capital on inventory that rarely gets used. Too little and you're experiencing stockouts that lose sales and damage customer relationships. The right amount depends on:
- How variable your demand is — volatile demand needs more buffer
- How reliable your suppliers are — unreliable supply chains need more buffer
- What a stockout costs you — if a stockout shuts down a production line, more buffer is justified
- What holding the inventory costs you — perishable goods have higher holding costs, so you want less buffer
For businesses managing perishable inventory, safety stock decisions are tightly connected to expiry management. Holding too much buffer of a short-dated product creates waste. This is where FEFO allocation becomes essential — your safety stock gets used in the right order.
5. FIFO (First In, First Out)
What It Is
FIFO is a stock rotation method where the oldest inventory (the first items received) is sold or used first. It's the most common stock allocation method and the default in most inventory systems.
When to Use FIFO
FIFO works well for:
- Non-perishable goods where receipt order is a reasonable proxy for priority
- Products with consistent shelf life across all batches
- Accounting purposes — FIFO is a widely accepted inventory valuation method
Limitations
FIFO assumes that the first items received should be the first items dispatched. This works fine for hardware or electronics, but breaks down for perishable goods where different batches might have different expiry dates. A delivery received on Monday might actually have a longer shelf life than one received the previous Friday.
For businesses dealing with expiry-sensitive products, FEFO is almost always the better choice.
6. FEFO (First Expiry, First Out)
What It Is
FEFO allocates stock based on expiry date rather than receipt date. The batch closest to expiring gets dispatched first, regardless of when it was received.
Why It Matters
FEFO is essential for any business handling perishable goods — food, beverages, pharmaceuticals, chemicals, cosmetics. It directly reduces waste by ensuring shorter-dated stock is used before it expires.
Example: You receive Batch A of yogurt on Monday (expires March 20) and Batch B on Wednesday (expires March 15). Under FIFO, you'd use Batch A first because it arrived first. Under FEFO, you'd use Batch B first because it expires sooner. This prevents Batch B from expiring unused.
Implementing FEFO
FEFO requires capturing expiry dates at the point of receipt for every batch. This adds a step to your receiving process, but the waste reduction and compliance benefits are substantial. A good inventory management system automates FEFO allocation — when a pick list is generated, the system automatically selects the shortest-dated batch.
For a detailed comparison of these two methods, including real-world scenarios and implementation guidance, see our comprehensive FEFO vs FIFO guide.
7. Cycle Counting
What It Is
Cycle counting is an inventory auditing method where you count a small subset of your inventory on a rotating schedule, rather than counting everything at once in a full stock take.
Instead of shutting down the warehouse once a year for a complete physical count, you might count 50 items per day, cycling through your entire inventory over a quarter. The warehouse stays operational, discrepancies are caught earlier, and accuracy improves continuously.
How to Structure Cycle Counts
The most effective approach ties cycle counting back to ABC analysis:
- A items: Count monthly or even weekly
- B items: Count quarterly
- C items: Count annually or semi-annually
This ensures your highest-value items are verified most frequently, while low-value items still get checked, just less often.
Benefits Over Annual Stock Takes
Traditional annual stock takes are disruptive, expensive, and tell you about accuracy problems months after they occurred. By the time you discover that your system says you have 500 units but the shelf only has 420, you've been making purchasing and sales decisions based on wrong data for months.
Cycle counting catches discrepancies in days or weeks, not months. The corrections are smaller, the root causes are easier to identify (because the error happened recently), and your inventory accuracy stays consistently high rather than degrading over a year and being "reset" once.
For practical guidance on conducting effective counts, including preparation steps and variance handling, see our stock take guide.
8. Demand Forecasting
What It Is
Demand forecasting uses historical sales data, market trends, seasonal patterns, and other signals to predict future demand. It's the foundation for almost every other inventory decision — how much to order, when to order, how much safety stock to hold, and how to allocate warehouse space.
Methods
Qualitative forecasting relies on expert judgment, market knowledge, and customer feedback. It's useful for new products with no sales history, or when market conditions are changing in ways that historical data can't predict.
Quantitative forecasting uses mathematical models applied to historical data:
- Moving average: Averages demand over a recent period (e.g., last 12 weeks). Simple but doesn't account for trends.
- Exponential smoothing: Gives more weight to recent data. Better for trending demand.
- Seasonal decomposition: Identifies and adjusts for seasonal patterns. Essential for businesses with cyclical demand.
- Regression analysis: Correlates demand with external factors (economic indicators, weather, marketing spend).
Practical Application
For most businesses, the goal isn't perfect forecasts — it's forecasts that are less wrong than guessing. Even a basic moving average applied to your top 50 SKUs will improve purchasing decisions compared to gut feel.
Example: A beverage company notices that sales of their sparkling water increase 40% every December-February. Without a forecast, they order the same quantity year-round and face stockouts every summer. With a simple seasonal adjustment, they increase December orders by 40% and maintain availability through peak season.
Modern inventory software often includes built-in forecasting tools that automatically analyse your sales data and suggest reorder quantities. This removes the need for manual spreadsheet analysis and makes forecasting accessible even for small teams.
9. Min-Max Inventory
What It Is
Min-Max is one of the simplest reorder strategies. You set two thresholds for each product:
- Minimum (Min): When stock drops to this level, trigger a reorder
- Maximum (Max): Order enough to bring stock up to this level
The reorder quantity is always Max − Current Stock.
How to Set Min and Max Levels
Minimum should cover your demand during the lead time plus a safety buffer:
Min = (Average Daily Demand × Lead Time in Days) + Safety Stock
Maximum should be your Min plus the most cost-effective order quantity (often informed by EOQ):
Max = Min + EOQ (or preferred order quantity)
Example: You sell 20 units per day, your supplier's lead time is 10 days, and you want 5 days of safety stock.
- Min = (20 × 10) + (20 × 5) = 200 + 100 = 300 units
- If your preferred order quantity is 500 units, Max = 300 + 500 = 800 units
When stock hits 300, you order 500 units (or whatever brings you to 800).
Advantages
Min-Max is easy to understand, easy to implement, and works well for stable-demand products. It's also easy to automate — most inventory systems support Min-Max reorder rules out of the box. For small businesses transitioning from spreadsheets, Min-Max is often the first formal reorder strategy they implement, and it delivers immediate improvements. See our guide to inventory management for small business for more on getting started with formal inventory processes.
Limitations
Min-Max doesn't adapt well to changing demand. If demand increases, your Min might be too low (leading to stockouts). If demand decreases, your Max might be too high (leading to overstock). You need to review and adjust thresholds periodically — quarterly at minimum for B and C items, monthly for A items.
10. Vendor-Managed Inventory (VMI)
What It Is
Vendor-Managed Inventory shifts the responsibility for managing stock levels from the buyer to the supplier. The supplier monitors your inventory levels (usually through shared data or system access) and replenishes stock proactively, without you needing to place orders.
How It Works
In a typical VMI arrangement:
- You share your real-time inventory data with the supplier (or they access it through your system)
- The supplier monitors your stock levels and consumption rates
- When stock hits the agreed threshold, the supplier ships a replenishment order
- You receive the goods and the supplier invoices you
The key shift is that the supplier decides when and how much to ship, based on your actual consumption data rather than your purchase orders.
Benefits
- Reduced stockouts — the supplier has a financial incentive to keep you stocked (if you run out, they lose sales)
- Lower ordering costs — you're not spending time creating and managing purchase orders
- Better supplier forecasting — the supplier sees your actual demand patterns, which helps them plan their own production
- Fewer rush orders — proactive replenishment reduces emergency situations
When It Makes Sense
VMI works best when:
- You have a high volume, ongoing relationship with the supplier
- The product has relatively stable demand patterns
- The supplier has the technical capability to monitor your inventory (system integration or portal access)
- There's mutual trust — you're sharing sensitive data about your consumption
VMI is common in manufacturing settings where a key raw material supplier manages the replenishment of that material. It's also used in retail, where major FMCG brands manage shelf replenishment in large supermarkets.
Challenges
The main risk is loss of control. If the supplier over-ships to meet their own sales targets, you end up overstocked. Clear contractual terms around maximum inventory levels, minimum shelf life on delivered goods, and dispute resolution are essential.
How Technology Supports These Techniques
It's worth noting that most of these techniques existed long before inventory software. ABC analysis can be done in a spreadsheet. EOQ can be calculated with a calculator. Safety stock formulas work on paper.
But implementing them at scale — across hundreds or thousands of SKUs, with real-time data, across multiple locations, and with consistent execution by multiple team members — is where technology becomes essential.
Here's what modern inventory software automates for each technique:
- ABC Analysis: Automatically classifies products based on sales data, and reclassifies as demand patterns change
- EOQ: Calculates optimal order quantities based on your actual ordering costs, holding costs, and demand data — and recalculates as these inputs change
- Safety Stock: Sets dynamic safety stock levels based on demand variability and lead time variability from your transaction history
- Min-Max: Monitors stock levels continuously and triggers alerts or automatic purchase orders at reorder points
- FEFO/FIFO: Automatically allocates the correct batch when generating pick lists — no manual selection required
- Cycle Counting: Schedules counts, generates count sheets, records results, and highlights variances for review
- Demand Forecasting: Analyses historical sales data to project future demand, adjusted for seasonal patterns and trends
The point isn't that you need software to use these techniques. It's that software makes them practical for a real business operating at real scale with real time constraints.
Combining Techniques
No single technique solves every inventory problem. The most effective approach combines several:
| Technique | What It Solves | Combine With |
|---|---|---|
| ABC Analysis | Where to focus attention | Everything — it's the foundation |
| EOQ | How much to order | Min-Max, Safety Stock |
| Safety Stock | Buffer against uncertainty | EOQ, Demand Forecasting |
| Min-Max | When to reorder | ABC Analysis, Safety Stock |
| JIT | Reducing excess inventory | Demand Forecasting, strong supplier relationships |
| FIFO/FEFO | Stock rotation | Cycle Counting, Safety Stock |
| Cycle Counting | Maintaining accuracy | ABC Analysis |
| Demand Forecasting | Predicting future needs | Safety Stock, EOQ, Min-Max |
| VMI | Supplier-managed replenishment | ABC Analysis (typically for A items) |
A practical starting point: Use ABC analysis to classify your inventory. Apply EOQ and Min-Max rules to your A and B items. Set safety stock levels based on demand variability and supplier reliability. Implement cycle counting tied to ABC categories. Use FEFO if you handle perishable goods.
Getting Started
If you're managing inventory with spreadsheets or basic tools, you don't need to implement all ten techniques at once. Start with the two that deliver the most immediate value:
- ABC Analysis — understand which products deserve the most attention
- Min-Max with Safety Stock — set up formal reorder rules for your top items
From there, layer on cycle counting, demand forecasting, and more sophisticated techniques as your processes mature.
The right stock management software makes these techniques practical at scale. Calculating EOQ for 5 products in a spreadsheet is manageable. Calculating it for 5,000 products while accounting for seasonal demand, supplier lead time variability, and current stock levels requires automation.
Not sure if inventory management software is worth the investment? Use our free ROI calculator to estimate your potential savings based on your current inventory costs and processes.
Frostbyte Pro supports Min-Max reorder rules, cycle counting, FEFO allocation, and demand-driven replenishment out of the box. Start a free trial or explore the full feature set to see how these techniques work in practice.
For industry-specific guidance, see our guides to inventory management for manufacturers, inventory management for food manufacturers, and wholesale inventory management software.