Inventory: How Much Stock a Business Really Needs

Why are too much and too little stock both expensive?

In many small companies, the warehouse is run by feel. People order when a bin looks empty, and a bit more because the last delivery was late. The result is full shelves with parts nobody has needed for years, and next to them empty bins for exactly the items that are missing right now. Both cost money: one ties up cash, the other costs orders.

Since the supply crises of recent years, the debate has shifted further. For a long time, all inventory was considered waste; then buffers suddenly became a virtue. This leads to the guiding question of this analysis: How much inventory does a small company really need, and what does the right amount depend on?

To answer it, we first clarify the terms and introduce a classic thinking model, Harris’s order quantity and safety stock. Then we review what studies show about the link between inventory and company performance, weigh the lean against the buffered view, and derive a classification that justifies how much of each item should be in stock.

A full warehouse reassures the owner and worries the bank.

Inventory, safety stock, reorder point: the terms

Eliyahu Goldratt defined inventory broadly: it is all money tied up in the system, as the article on Goldratt’s theory of constraints describes. The warehouse is the most visible part of it. It buffers between procurement and consumption because goods rarely arrive exactly when they are needed.

• Replenishment time is the time from placing an order until the goods are available in the warehouse.
• Safety stock is the quantity held back for consumption peaks and late deliveries. Normally, it is not touched.
• The reorder point is the quantity at which a new order is placed. It equals consumption during the replenishment time plus safety stock.
• Days of supply indicate how many days the existing stock lasts at normal consumption.
• Holding costs include interest on the tied-up money, space, insurance, shrinkage, and the risk of goods becoming obsolete.

Inventory has a direct effect on liquidity. The cash conversion cycle measures the gap in days between paying for material and receiving the customer’s payment: days in inventory plus days receivable minus days payable. Every day goods spend longer in the warehouse lengthens this gap by one day. How this plays out with growing revenue is calculated in the analysis of why growth costs liquidity.

The thinking model: Harris’s order quantity and safety stock

In 1913, the engineer Ford Whitman Harris answered a question every buyer asks: how much do I order at once? Ordering large quantities rarely saves ordering costs, that is, the effort for quote, order, goods receipt, and invoice, but costs more in storage. Ordering small quantities often keeps the warehouse small but creates a lot of ordering effort. Harris showed that there is a quantity at which the sum of both costs is lowest (Harris 1913).

The formula is: optimal order quantity equals the square root of two times annual demand times cost per order, divided by holding cost per unit and year. An example: a company uses 2,400 units of a part per year. An order costs it 60 euros internally, and one unit in stock costs 2 euros a year. The optimal order quantity is then about 380 units, roughly six orders a year.

The main lesson lies not in the formula but in the chart. Around the optimum, costs are flat. Whether you order 300 or 450 units makes hardly any difference. By contrast, whoever buys 1,200 units at once because the supplier offers a small volume discount pays more than they save, unless the discount exceeds the additional holding costs. Rough values are therefore enough, as long as you are not far off.

Harris assumed even consumption and punctual delivery. In reality both fluctuate, and that is what safety stock is for. In the example: the company uses an average of 10 units a day, the replenishment time is 12 days, and it holds back 6 days of consumption as safety, that is, 60 units. The reorder point is then 10 times 12 plus 60, or 180 units. Like the fuel gauge in a car, the warning light does not come on when the tank is empty but when what is left will still reach the next gas station.

What studies show about inventory and company performance

Whether less inventory makes companies more successful was examined by Eroglu and Hofer (2011) using a large data set of US manufacturing companies. Their methodological core: they compared companies only within their industry, because a machine builder naturally needs more inventory than a food producer. If all industries are lumped together, they argue, the different patterns mask each other.

The result is more nuanced than the common lesson that less is always better. In two thirds of the 54 industries studied, they found a measurable relationship between lean inventory and performance. In most of these cases it was curved: less inventory improved performance up to a point, after which performance declined again. So there is an optimum, and it is possible to go below it.

A follow-up study by the same authors shows that the benefit of lean inventory depends on the environment: in turbulent, hard-to-predict markets it turns out differently than in calm ones (Eroglu and Hofer 2014). An analysis of 16,022 observations of Japanese companies found a positive relationship between lean inventory and profitability that was stronger in companies with more intensive use of information technology (Kamada 2025).

All three studies look at larger companies with published figures, not small trade or retail businesses. Their direction is still transferable: reducing inventory usually pays off, but not without limit, and whoever knows their consumption more precisely can manage with less buffer.

Waste or insurance? Two perspectives

The first view comes from lean production thinking. Inventory is one of the seven types of waste there, and not only because it ties up money. It hides problems: whoever has enough in stock does not notice that a supplier is unreliable or that their own process is stalling. The article on lean in the office applies this idea to piles of open cases.

The second view comes from resilience research. Buffers that are not needed in normal operations are called organizational slack there, and they are among the preconditions for surviving crises. Whoever had a few weeks of stock of critical parts during the material shortages could deliver while others waited. The analysis of geopolitics as a business risk shows how strongly these shortages fluctuated.

I consider both views right, but for different items. Eroglu and Hofer’s findings fit this reading: there is an optimum, and it is not zero. It follows that inventory should not be cut or raised across the board but justified item by item. Resilience costs margin, so you afford it deliberately for a few positions whose absence stops the business.

The ABC-XYZ classification: how much buffer each item needs

The tool for this justification is the ABC-XYZ classification. It combines two questions. The ABC classification follows the same Pareto idea as the ABC analysis of customers in the guide to ABC analysis of customers: few items account for a large share of consumption value, often around 70 to 80 percent. The XYZ classification asks how evenly an item is consumed: X stands for even, Y for fluctuating, Z for sporadic.

One exception applies to all cells: a part without which an order comes to a standstill and which only one supplier provides gets a deliberately higher safety stock, even if it is cheap. Here stock planning overlaps with the Kraljic matrix from the guide to evaluating suppliers, where such parts are called bottleneck items.

1. Determine consumption value

   Multiply each item’s annual consumption by its purchase price and sort in descending order. The items that together make up about 75 percent of the value are A.

2. Assess variability

   Compare monthly consumption over a year. If it is almost always close to the average, the item is X; if it fluctuates noticeably, Y; if it is needed only occasionally, Z.

3. Record replenishment time

   Note the actual time from order to goods receipt for A and B items, not the promised time.

4. Set the reorder point

   Calculate the reorder point for each A and B item from daily consumption, replenishment time, and safety stock, and record it in the warehouse or system.

5. Check slow movers

   Once a year, list all items without consumption in the last twelve months and decide whether to sell, return, or write them off.

What one day of supply costs: a worked example

A company holds an average of 120,000 euros of goods in stock, equivalent to 60 days of supply. If holding costs are set at 20 percent of inventory value per year in the example, the warehouse costs about 24,000 euros annually for interest, space, insurance, shrinkage, and obsolescence. How high this rate is in your own company depends strongly on industry and goods.

If the company reduces days of supply to 45 through better reorder points and clearing out slow movers, inventory falls to 90,000 euros. That releases 30,000 euros that no longer need financing, and holding costs fall by 6,000 euros a year. At the same time, the cash conversion cycle shortens by 15 days. What matters is where you save: on C items and slow movers, not on the safety stock of bottleneck parts.

What follows beyond the warehouse, and where the limits are

As shown above, the question of the right inventory is not one of conviction but of justification per item. A rule follows that reaches beyond the warehouse: buffers make sense where a disruption is expensive and likely, and are superfluous where it is cheap or rare. The same logic applies to time buffers in planning and to cash reserves.

Inventory is also a mirror of other processes. A high safety stock for a part can indicate an unreliable supplier, a growing warehouse can indicate ordering by feel. Whoever wants to reduce inventory should therefore look at the causes first instead of just ordering less.

The limits are clear. Harris’s order quantity rests on assumptions that rarely hold exactly. The studies cited look at large companies. And the figures in the worked example are freely chosen. For your own decision, your own consumption data counts, and it is usually already in the inventory system or the invoices.

Conclusion: how much inventory does a business need?

The question was
much inventory a small company really needs and what the right amount depends on. The answer is: as much as consumption during the replenishment time requires, plus a safety stock that matches the item’s variability and importance. Harris’s order quantity shows that costs are flat around the optimum, so rough values are enough.

As research shows, there is an optimum, and it is not zero. Lean inventory usually improves performance, but only up to a point. That is why inventory is not cut across the board but justified item by item: tight for expensive, evenly consumed items, generous for cheap ones, deliberately buffered for parts without which the business stands still. The sober observation is: the right warehouse is not the smallest one but the one where you can say for every bin why it is as full as it is.

First steps for this week

1. Determine total inventory in euros and divide it by daily consumption to get days of supply.
2. Sort items by consumption value and mark the A items.
3. Note the actual replenishment time for the ten most important items.
4. Set a reorder point for these ten and write it on the bin or in the system.
5. List all items without consumption in the last twelve months and decide on each one.