Forecasting

Using Optimal Order Quantity for Improved Inventory

Inventory management is a huge part of any retail,  e-commerce, or wholesale business’s assets and supply chain strategy. But while it’s necessary for a business to operate, inventory requires careful calculations to ensure it meets demand without becoming too much of an expenditure and a drag on cash flow.

Achieving this balance requires merchants to engage in proper inventory planning to make sure they have the right amount of stock at the right time. If performed efficiently, inventory planning can help your business: 

  •     Avoid stockouts
  •     Minimize unnecessary overstock and deadstock 
  •     Optimize inventory in multiple locations
  •     Improve stock turnover
  •     Make complex calculations simple
  •     Prevent delays and eliminate mistakes
  •     Accurately predict production, shipping, and lead times
  •     All of which lead to increased cash flow and revenue 

A critical component of inventory planning is accurately calculating optimal order quantity, which helps businesses know when and what to order to maintain customer satisfaction and profitability while avoiding unnecessary storage, administrative, and insurance costs.

What is optimal order quantity?

Optimal order quantity, also known as the economic order quantity (EOQ), represents the ideal amount of inventory a business should have at any given time to meet demand without holding too much excess stock. Calculating optimal order quantity using an economic order quantity formula will provide you with the precise number of units to purchase for each product in your catalog and can help you determine your reorder point (ROP) when you should submit the next purchase order to your supplier.

Factors to consider for optimal order quantity

Optimal order quantity is heavily contingent on a variety of factors. How often you turn over inventory, the sales velocity of certain products, the manufacturing and lead times of your suppliers, minimum order quantities, your available shipping transit times, and more will all affect your business’s optimal order quantity.

Before attempting to calculate your EOQ, there are a few inventory metrics you must know:

Annual demand (also known as annual usage)

Annual demand refers to how much customer demand there is for a particular product in any given year. You can determine this by looking at historical data points such as turnover ratio, previous reorder points, and past purchase orders. This will give you a clear picture of how many units you’ve sold year-over-year.

Order costs (also known as setup costs)

Order costs are all the costs associated with placing an order with your supplier. These include administrative costs involved in creating purchase orders and invoices, packaging and delivery costs, product inspections, receiving shipments at the warehouse, and other fulfillment costs that go into every order placed.

Holding costs

Your annual holding cost refers to how much it costs to keep the stock for one year. These include any expenses related to storing inventory as well as opportunity costs from inventory retention, including rent and operational fees for any warehousing or storage, interest on loans to purchase stock, insurance premiums, warehouse employee salaries, and depreciation costs. To calculate holding costs, use the following formula:

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

You add up employee salaries, storage and other inventory costs, opportunity costs, and depreciation costs, then divide the sum by the total value of your annual inventory. The answer is your inventory holding cost (expressed in a percentage).

Once you’ve determined these three values, you have the information necessary to calculate optimal order quantity.

Automated purchasing suggestions

Let Inventory Planner work out your optimal order quantity

Get my demo

Optimal order quantity formula

To calculate optimal order quantity (economic order quantity), you can use the following EOQ formula:

the square root of (2[DO] / H) = EOQ (optimal order quantity)

Where D = Annual unit demand, O = Cost per order, and H = Holding cost per unit 

  •     First, you multiply annual unit demand (D) by the cost per order (O)
  •     Then you multiply that answer by two.
  •     Next, you take that number and divide it by your holding costs per unit (H)
  •     Finally, take the square root of that number to get your EOQ (optimal order quantity)

For example, if you sell 500 shirts a year, and you pay $6 per unit for an order, and $8 a unit to store the inventory for a year, your EOQ formula will look like this:

The square root of (2 x [500 shirts x $6 ordering cost]) / $8 holding cost = ~9.7

According to the formula, your optimal ordering quantity, or EOQ, is ~10 units. This amount will meet your customer demand without incurring excessive overhead costs.

Assumptions affecting optimal ordering quantity’s accuracy

While it is a useful calculation, the economic order quantity formula requires you to make six important assumptions that can negate its accuracy in practical applications:

  •     Demand will remain constant. This assumption becomes problematic when dealing with seasonal items, or in markets where customer demand is continually and rapidly shifting due to various factors like influencer culture, macroeconomic changes, and new emerging sales channels.
  •     The unit prices remain constant. This assumption does not hold true when production and shipping costs fluctuate.
  •     The holding cost per unit remains constant. This assumption does not hold true when inflation is high and overhead costs are subject to increases.
  •     The setup costs remain constant.
  •     Orders are never delayed. This assumption does not account for supply chain disruptions due to reduced shipping capacities, warehouse space and labor shortages, as well as global events that may impede trade and shipping routes.
  •     There are no discounts on any of your orders. This assumption doesn’t work for businesses with strong seasonality, including retail holidays like Black Friday.

If any of these assumptions change during any given time period, and many will, it may affect the accuracy of your calculated optimal order quantity.

How Inventory Planner can help

As you can see, calculating optimal order quantity and incorporating it into how and when you place your orders requires sophisticated calculations that factor in many dynamic variables to achieve accuracy. With today’s fast-moving customer demand, highly-disrupted supply chains, and shifting lead times, it’s nearly impossible to keep your calculations up-to-date when done manually, especially if you have a large catalog or launch new products often. To ensure accuracy, you need automated, reliable inventory planning software that does all the heavy lifting for you. That’s where Inventory Planner comes in.

Say goodbye to manually computing complex formulas and keeping track of a variety of shifting variables for each of your SKUs. Inventory Planner automatically calculates how much inventory you need and when to place each order. It syncs with your business’s tech stack, using product and sales data from your online sales channels, accounting, shipping, inventory management, warehouse management, order management, ERP, and any other software you use to ensure you always have up-to-date insights. It also factors in critical fluctuations like seasonality, customer demand shifts, promotions, and marketing activities for ultimate accuracy. 

Not only does Inventory Planner tell you what to order and when to order, but it also offers insightful, customizable inventory performance reporting. Its 200+ meaningful metrics plus additional marketing metrics pulled from Google Analytics allow you to make truly data-driven decisions. So, ditch the spreadsheets and manual data entry for intuitive, dynamic inventory planning software that can streamline your economic order quantity process and save you time and money on inventory management.