What Is Economic Order Quantity (EOQ)? Formula, Examples & Assumptions

What Is Economic Order Quantity (EOQ)? Formula, Examples & Assumptions

Want to avoid stockouts, increase customer satisfaction, and boost profits? You’ll need to calculate your optimal quantity first.

Direct-to-consumer brands (like yours) need to know the most efficient way to stock up and meet customer demand – without collecting extra, unnecessary costs.

Luckily, economic order quantity finds that sweet spot, so you can stock up and maximize your profits. Here’s how.


What is optimal order quantity?

In inventory management, economic order quantity (or optimal order quantity) is the ideal amount of inventory retailers should restock to minimize their order and carrying costs.

Here, order costs refer to the processing fees and transportation expenses accumulated when you place a purchase order.

Meanwhile, carrying costs encompass any fees associated with storing that inventory once it arrives at your warehouse. It’s important to note that both of these costs eat away at your profit margins.

But what does this have to do with EOQ?

If you place small purchase orders frequently, your ordering costs will increase (because you’ll need to place more POs). However, your storage costs will decrease (because you’ll keep less inventory on hand).

Plus, in this scenario, you risk understocking, which can lead to stockouts and missed sales opportunities.

On the flip side, if you place bigger, bulk orders less frequently, your ordering costs decrease, and your storage costs increase. But you risk overstocking, which ties up cash flow in excess stock and makes pivoting when things go wrong (think: shortages in your supply chain) harder.

Somewhere in the middle is your EOQ. With it, you can maintain optimal inventory levels, reducing your ordering, receiving, and storage costs and maximizing your profitability as a result.

📝 Note
Optimal order quantity tells you how much to restock, not when. To determine when to place your next purchase order, calculate your reorder point: reorder point = [(daily unit sales x lead time) + safety stock level]

 


How to calculate optimal order quantity

To calculate EOQ, use the economic order quantity formula:

EOQ = √[(2 × annual demand × cost per order)/(holding cost per unit)]

Keep in mind: EOQ is calculated at the product level. So, you’ll need to re-run the formula for every SKU you carry.

Variables in the EOQ formula

Let’s quickly break down annual demand, cost per order, and holding costs. Plus, how you can gather this information.

Variable 1: Annual unit demand

Annual unit demand is the number of units you sell annually of a specific product.

To find this number, check your inventory system or order records to see how many units you sold last year.

If this information is unavailable (maybe you’re launching a new product), feel free to use your forecasted demand instead.

Variable 2: Costs per order

Costs per order include any expenses related to purchasing and receiving new inventory. This includes purchase order processing fees, import duties, and transportation costs (just to name a few).

So, how can you calculate your cost per order? Cogsy can help!

How? Within the purchase order feature, factor in any necessary adjustments (think: shipping costs). The total cost after all those adjustments is your cost per order.

🔥 Tip
By adjusting your purchase order costs in Cogsy, you’re one step closer to tracking COGS on a per SKU and per vendor basis. That way, you can start improving your contribution margins accordingly. Try for free.

 

Variable 3: Holding costs per unit

Holding costs (or carrying costs) refer to any expenses accrued to store your inventory.

To calculate your inventory carrying costs, use the formula:

holding cost = (employee salaries + storage costs + opportunity costs + depreciation costs) / total value of annual inventory

Remember: For the EOQ formula, you need holding costs per unit.

The easiest way to get this number is by calculating your holding costs at a product level (using the above formula).

Then, divide your answer by the total number of units you held of that product in the past year (your inventory system should have this number) to get holding costs per unit.


Economic order quantity example

Admittedly, calculating EOQ can be confusing. So, let’s walk through a real-life example.

Say one of your best-selling products is lavender candles. You sold 1,000 last year.

Your company pays $2 fixed costs per order and $4 annually to hold one unit at your warehouse.

Using the EOQ formula, you get an EOQ of 31.6. Meaning, your optimal order quantity for lavender candles is 32.

By restocking this amount, you should hypothetically be able to meet demand and lower overhead costs.

But that’s only true if the formula’s assumptions are correct (more on this in a second).


The problem with economic order quantity

The basis for the economic order quantity model (wrongfully) assumes that six factors remain constant in the calculated period.

Wrong assumption 1: Product demand remains constant

EOQ assumes that customer demand remains constant and that growth remains stagnant.

However, most ecommerce brands aim to scale. Meaning, they’re constantly looking to increase customer demand, which throws off this calculation.

Wrong assumption 2: Holding costs are fixed

The fees to store your unsold inventory are seldom fixed costs. And generally, the longer stock goes unsold, the more expensive it gets.

So, any slow in sales can increase your carrying costs and affect EOQ.

Wrong assumption 3: Unit order prices will stay the same

EOQ assumes you won’t see a supplier price increase in the calculated period.

However, in times of higher inflation (like in 2023), someone has to eat the higher costs. And unless you negotiate vendor terms that prevent your supplier from unexpectedly raising their prices, that person will likely be you.

Wrong assumption 4: Set-up costs are fixed

Set-up costs include any expenses related to ordering your inventory, including packaging and delivery. But similar to your unit order prices, these costs are subject to change – especially during periods of high inflation or supply chain disruptions.

Wrong assumption 5: Incoming orders are never delayed

For the EOQ formula to work, your order lead time must be completely predictable, and orders must arrive on time every time. Otherwise, you run the risk of stockout.

That said, even the best supply chain is subject to unpredictable delays from time to time.

Wrong assumption 6: No products were bought at a discount

EOQ assumes that none of your products were sold to you at a discounted rate. Or, if they were, it needs you to always get that quantity discount.

However, optimal quantities generally do not agree with bulk volumes, so you’ll need to brace yourself for higher unit costs if you’re using EOQ.

Perhaps needless to say, all six constants are rarely something ecommerce can rely on. As such, this formula can be a helpful guide for retailers but tends to be misleading in application.

So, what’s a better way to maintain optimal inventory levels? Lean on Cogsy for streamlined restocking and headache-free inventory management.


Stay on top of your inventory levels with Cogsy

Cogsy is the end-to-end purchasing platform giving Shopify merchants and Amazon sellers more inventory control.

With its actionable dashboard, keep a 24/7 eye on your inventory levels. The dashboard will show you what to restock next and when.

But there’s no need to babysit this data. Whenever you’re running low, Cogsy will email you a replenish alert, letting you know it’s the ideal time to place your next PO.

And thanks to handy restock recommendations, drafting this purchase order only takes five minutes with Cogsy.

Unlike the EOQ calculation, these recommendations factor in demand fluctuations (think: seasonality), safety stock, and potential supply chain delays for peace of mind. So, you can stock up to meet actual demand while still avoiding extra operational costs.

Even better, you can monitor where this purchase order is (from draft to delivery) by connecting the shipment’s unique tracking URL.

And if any delays creep up along your supply chain (it happens to the best brands), you’ll know right away. So, you can easily side-step stockouts by transferring inventory from another location or selling on backorder. That way, this mishap doesn’t hinder your growth goals.

Best part? DTC brands that sell with Cogsy generate 40% more revenue on average and save 20+ hours weekly on inventory management.

But don’t take our word for it – try Cogsy free for 14 days.

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Economic order quantity (EOQ) FAQs

  • What is the purpose of economic order quantity?

    Economic order quantity helps retailers order the ideal amount to get back to satisfy customer demand and maximize profits by maintaining the optimal stock level for every product sold.

  • What are the advantages of economic order quantity?

    Some advantages of economic order quantity include reducing dead stock, preventing stockouts, reducing inventory costs, and improving the retailer’s bottom line.

  • What are the limitations of economic order quantity?

    Economic order quantity can often misguide retailers because it’s limited by six (typically wrong) assumptions:

    1. Product demand will remain constant
    2. Holding costs are fixed
    3. Unit prices will stay the same
    4. Set-up costs are fixed
    5. Orders will always arrive without delays
    6. No products were bought at a discount
  • What is the difference between optimal quantity and minimum order quantity?

    Economic order quantity is the ideal amount retailers should restock each product to minimize their order and carrying costs. Meanwhile, minimum order quantity (MOQ) is the minimum amount of product you must buy from your supplier at a time. It’s important to note that your brand’s EOQ and your supplier’s MOQ might not agree.

  • What is optimal safety stock quantity?

    Safety stock is the extra product you keep on hand to buffer a stockout situation. Your optimal safety stock quantity depends on your inventory velocity, current and future demand, and supplier lead times. To calculate, use the following formula:

    safety stock = (maximum daily use × maximum lead time) – (average daily use × average lead time)