Make your own free website on


Optimizing Economic Order Quantity

Home | What is Economic Order Quantity? | Its Cost Components | EOQ Model with Purchases | Assumptions of the Model | Optimizing Economic Order Quantity | Graphical Solutions | Sample Problems | Answers

Yellow file folder overflowing


Optimizing Economic Order Quantity (EOQ)

By Dave Piasecki

As published in the January, 2001 issue of Solutions

     Inventory models for calculating optimal order quantities and reorder points have been in existence long before the arrival of the computer.  When the first Model T Fords were rolling off the assembly line, manufacturers were already reaping the financial benefits of inventory management by determining the most cost effective answers to the questions of  When? and How much?.  Yes long before JIT, TQM, TOC, and MRP, companies were using these same (then unnamed) concepts in managing their production and inventory.  I recently read Purchasing and Storing, a textbook that was part of a “Modern Business Course” at the Alexander Hamilton Institute in New York.  The textbook published in 1931 (that’s right 1931) was essentially a how to book on inventory management in a manufacturing environment.  If you’re wondering why I would want to read a 70-year-old business text, my answer would be that the fundamental concepts of managing a business change very little with time, and reading about these concepts in a vintage text is a great way to reinforce the value of the fundamentals.  The occasional reference to “The War” (referring to WWI) also keeps it interesting and the complete absence of acronyms is refreshing.

     As you may have guessed, this 70-year-old book contained a section on Minimum Cost Quantity, which is what we now refer to as Economic Order Quantity (EOQ).  I can imagine that in the 1930’s an accountant (or more likely a room full of accountants) would have calculated EOQ or other inventory related formulas one item at a time in a dimly lit office using the inventory books, a mechanical adding machine and a slide rule.  Time consuming as this was, some manufacturers of the time recognized the financial benefits of taking a scientific approach to making these inventory decisions.

     So why is it that, in these days of advanced information technology, many companies are still not taking advantage of these fundamental inventory models?  Part of the answer lies in poor results received due to inaccurate data inputs.  Accurate product costs, activity costs, forecasts, history, and lead times are crucial in making inventory models work. Ironically, software advancements may also in part to blame. Many ERP packages come with built in calculations for EOQ which calculate automatically. Often the users do not understand how it is calculated and therefore do not understand the data inputs and system setup which controls the output. When the output appears to be "out of whack" it is simply ignored.  This sometimes creates a situation in which the executives who had purchased the software incorrectly assume the material planners and purchasing clerks are ordering based upon the systems recommendations.  I should also note that many operations will find these built-in EOQ calculations inadequate and in need of modifications to deal with the diversity of their product groups and processes.

     Corporate goals and strategies may sometimes conflict with EOQ.  Measuring performance solely by inventory turns is one of the most prolific mistakes made in the name of inventory management.  Many companies have achieved aggressive goals in increasing inventory turns only to find their bottom line has shrunk due to increased operational costs.  

     EOQ is essentially an accounting formula that determines the point at which the combination of order costs and inventory carrying costs are the least. The result is the most cost effective quantity to order.  In purchasing this is known as the order quantity, in manufacturing it is known as the production lot size.

While EOQ may not apply to every inventory situation, most organizations will find it beneficial in at least some aspect of their operation.  Anytime you have repetitive purchasing or planning of an item, EOQ should be considered. Obvious applications for EOQ are purchase-to-stock distributors and make-to-stock manufacturers, however, make-to-order manufacturers should also consider EOQ when they have multiple orders or release dates for the same items and when planning components and sub-assemblies.  Repetitive buy maintenance, repair, and operating (MRO) inventory is also a good application for EOQ.  Though EOQ is generally recommended in operations where demand is relatively steady, items with demand variability such as seasonality can still use the model by going to shorter time periods for the EOQ calculation.  Just make sure your usage and carrying costs are based on the same time period.

     Doesn’t EOQ conflict with Just-In-Time?  While I don’t want to get into a long discussion on the misconceptions of what Just-In-Time (JIT) is, I will address the most common misunderstanding in which JIT is assumed to mean all components should arrive in the exact run quantities “just in time” for the production run.  JIT is actually a quality initiative with the goal of eliminating wasted steps, wasted labor, and wasted cost. EOQ should be one of the tools used to achieve this. EOQ is used to determine which components fit into this JIT model and what level of JIT is economically advantageous for your operation.  As an example, let us assume you are a lawn equipment manufacturer and you produce 100 units per day of a specific model of lawn mower.  While it may be cost effective to have 100 engines arrive on your dock each day, it would certainly not be cost effective to have 500 screws (1 days supply) used to mount a plastic housing on the lawn mower shipped to you daily.  To determine the most cost effective quantities of screws or other components you will need to use the EOQ formula.

The basic Economic Order Quantity (EOQ) formula is as follows:


The Inputs


     While the calculation itself is fairly simple the task of determining the correct data inputs to accurately represent your inventory and operation is a bit of a project.  Exaggerated order costs and carrying costs are common mistakes made in EOQ calculations.  Using all costs associated with your purchasing and receiving departments to calculate order cost or using all costs associated with storage and material handling to calculate carrying cost will give you highly inflated costs resulting in inaccurate results from your EOQ calculation.  I also caution against using benchmarks or published industry standards in calculations.  I have frequently seen references to average purchase order costs of $100 to $150 in magazine articles and product brochures.  Often these references trace back to studies performed by advocacy agencies working for business that directly benefit from these exaggerated (my opinion) costs used in ROI calculations for their products or services.  I am not denying that some operations may have purchase costs in this range, especially if you are frequently re-sourcing, re-quoting, and/or buying from overseas vendors. However if your operation is primarily involved with repetitive buying from domestic vendors — which is more common — you’ll likely see your purchase order costs in the substantially lower $10 to $30 range.

As you prepare to undertake this project keep in mind that even though accuracy is crucial, small variances in the data inputs generally have very little effect on the outputs.  The following breaks down the data inputs in more detail and gives insight into the aspects of each.



     EOQ calculations are frequently used in business, both by production, purchasing and inventory managers. This tool provides everything it takes to make reliable calculations. In addition, it automatically computes the reorder point (= the amount of inventory at which new orders must be placed) and order cycle time in days, both if there is a leadtime (= period between the placement of an order and its receipt in inventory) or none. An automatically generated chart based on input data can be directly exported to any presentation.                                                                  

Time ROI                                                                           

             It takes on average 8 hours to develop the model and to create the resulting chart. By using, you will save a minimum of 6 hours developing the initial template. You will, however, need to input the annual product quantity demand, product price per unit, and selected costs to calculate the EOQ and Reorder Timing.  

Buildingized computer

back to top